Effectiveness Improvement in Manufacturing Industry; Trilogy Study and Open Innovation Dynamics

Journal of Open Innovation: Technology, Market, and Complexity

Article Effectiveness Improvement in Manufacturing Industry; Trilogy Study and Open Innovation Dynamics

Ashwani Tayal 1 , Nirmal Singh Kalsi 2, Munish Kumar Gupta 3,4 , Danil Yurievich Pimenov 4 , Murat Sarikaya 5 and Catalin I. Pruncu 6,7,*

1 Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Jalandhar 144603, India; [email protected] 2 Department of Mechanical Engineering, Beant College of Engineering &Technology, Punjab 143521, India; [email protected] 3 Key Laboratory of High Efﬁciency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan 250000, China; [email protected] 4 Department of Automated Mechanical Engineering, South Ural State University, Chelyabinsk 454080, Russia; [email protected] 5 Department of Mechanical Engineering, Sinop University, Sinop 57000, Turkey; [email protected] 6 Department of Mechanical Engineering, Imperial College London, London SW7 2AZ, UK 7 Design, Manufacturing & Engineering Management, University of Strathclyde, Glasgow G1 1XJ, UK * Correspondence: [email protected] or [email protected]

Abstract: The purpose of this investigation is to compute overall equipment effectiveness (OEE) in the small-scale industry. The novel approach is introduced to detect bottlenecks by which OEE can be improved. This study attempts to help small-medium enterprises in analyzing performance in a better way. The automotive industry was chosen for conducting the research. The present

study is comprised of three phases. In the ﬁrst phase, OEE was computed and compared with world-class manufacturing. The second phase included three-level of Pareto analysis followed by

Citation: Tayal, A.; Kalsi, N.S.; Gupta, making fishbone diagram to mitigate the losses. The third phase conducted improved OEE in the M.K.; Pimenov, D.Y.; Sarikaya, M.; industry. There are seven major losses present in the industry that adversely affect the effectiveness Pruncu, C.I. Effectiveness of machine in any industry. This approach can reduce these losses and improve the quality, asset Improvement in Manufacturing utilization (AU), OEE, total effective equipment performance (TEEP) and productivity of the machine. Industry; Trilogy Study and Open The study exposes that Pareto analysis uncovers all the losses and works on the principle of 80/20 Innovation Dynamics. J. Open Innov. rule. The major losses were thoroughly explored with the help of the fishbone diagram and solutions Technol. Mark. Complex. 2021, 7, 7. were implemented at the shop floor. As a result, availability, performance, quality, OEE, AU, and https://doi.org/10.3390/ TEPP show improvements by 4.6%, 8.06%, 6.66%, 16.23%, 4.16%, and 14.58%, respectively. The joitmc7010007 approach offers a good opportunity for both researchers and small-medium enterprises around the world to analyze the indicators of production losses, performance, and productivity in the Received: 11 November 2020 manufacturing industry. Accepted: 25 December 2020 Published: 30 December 2020 Keywords: manufacturing industry; pareto analysis; fishbone diagram; asset utilization; overall

Publisher’s Note: MDPI stays neu- equipment effectiveness tral with regard to jurisdictional clai- ms in published maps and institutio- nal affiliations. 1. Introduction The numerous considerations such as demand for a quality product at cost-conscious value, competition, exploration of new technology make reliability more critically during Copyright: © 2020 by the authors. Li- censee MDPI, Basel, Switzerland. their design [1]. Recent advancements reveal an incredible improvement in the use of This article is an open access article reliability engineering due to more intricate and advanced systems, which cater to the distributed under the terms and con- needs of the customer-driven market inefficient manner [2]. The reliability engineering was ditions of the Creative Commons At- categorized into the specialized area. Data-driven and multi-function governance team are tribution (CC BY) license (https:// two characteristics which lead the world-class manufacturing system by promoting higher creativecommons.org/licenses/by/ efficiency and satisfaction among internal and external customers. Reliability engineering 4.0/). faces a wide variety of challenges in today’s industrial transformation. Reliability shows

J. Open Innov. Technol. Mark. Complex. 2021, 7, 7. https://doi.org/10.3390/joitmc7010007 https://www.mdpi.com/journal/joitmc J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 2 of 21

impressive progress for maintaining the industries, but the numerous factors such as intricacy, cost comparison, and competition make reliability more difficult in this era. Automotive trains, nuclear devices, space outposts, aviation, computers, and railways are some of the spiral typical systems that affect our daily lives, and, therefore, they need to be more reliable to support satisfactory operation without fail. These allocated systems are seriously affected, directly or indirectly, by specific factors i.e., high procurement cost, complexity, safety, reliability, quality, and universal competition. The reliability factors reveal that the fruitful execution of product design and its operation phase-only results from the coordination among distinct specialists specifically from a quality, maintenance, and reliability departments, having cross-functional knowledge to retain the triumph of industrial establishment [3]. Manufacturing systems are generally recognized by sequential production activities involved in the conversion of raw material into tangible goods as initiated by planning and completed by sales and management. These systems are capitalized with a considerable amount for design and implementation of numerous types of equipment and machinery to nurture production movements at consistent supply with marginal scrap. Manufacturing systems are labeled with distinct features such as delivering essential human services, building nations’ prosperity and strides for global reconciliation and human contentment. The integration and coordination among various flows (the flow of material; the flow of data; and the flow of cost) result in effective manufacturing movements. Material flow includes conversion of raw material into tangible goods, information flow comprises of planning and control of production movements, and cost flow embraces economical production. The flow of information, material, and cost play vital role in effective manufacturing system; hence, enhancing equipment reliability is the promising and major targeted area in the industry to maintain healthy relationships among production and market demand [4]. Equipment failure triggers two major issues such as non-production hours and non-compliance of demand for products. The severity of these issues can result in shrinking profitability and even company move out from the race of business. Maintainability can be deemed as an assistance tool to foster these issues; however, efficient and precise equipment directs to manufacture best quality and quantity commodities at right time for the market. The prime objective of an effective maintenance plan is to achieve profitable production by reducing downtime in the plant. The unqualified labor force, unskilled operators, inadequate machine scheduling and planning are some of the major issues experienced by small scale industries which result in ineffectiveness of the manufacturing system [5–7]. Inadequate scheduling, planning, and unskilled operators prove more stoppages, less production time, and more quality defects; hence, these minor concerns must be properly addressed to counter all the ill effects on the manufacturing system. Numerous techniques, tools, and plans are available such as affinity diagram, tree diagram, matrix diagram, arrow diagram, and process decision program categorized under management techniques. Cause and effect diagram, Pareto chart, check sheet, control chart, histogram, and scatter diagram can be shown as basic quality tools. Further, total quality management, total productive maintenance, just in time, lean production, and Kaizen can be sorted under philosophies. The success rate of any industry depends on accumulating data analytics for effective use of 5M (man, machine, material, methods, money) and uses this data for process improvement. Generally, alternative approaches are deliberate to mitigate the problems that occur repeatedly in the system. Existing works of literature are primarily fixated on the use of different techniques in numerous industries. Some of these studies are summarized as follows. Purba et al. [8] analyzed the Overall Equipment Effectiveness (OEE) with total productive maintenance method on cutting. For this, the researchers conducted a case study in the manufacturing industry. Their outcomes indicated that the highest OEE was 86.05% in July 2015 and the lowest OEE was 79.58% in August 2015. Chong et al. [9] presented the implementation of maintenance Failure Mode and Effect Analysis (FMEA) to develop OEE in a manufacturing company. The FMEA was performed with a five-step approach on a bottleneck process. Their outcomes showed that J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 3 of 21

by taking the necessary precautions, machine availability can be improved and so high OEE can be achieved. Kapuria et al. [10] conducted a root cause analysis and productivity improvement in Bangladesh by using Kaizen implementation. They used Pareto analysis to identify defective items. With the implementation of the Kaizen implementation, the efficiency of the factory’s production line was increased from 45% to 60%. Nallusamy [11] studied the effectiveness and implementation of an independent maintenance system in a machine shop to improve OEE by using Total Productive Maintenance (TPM) and 5S implementation which are described as Sort, Set in order, Shine, Standardize, and Sustain. According to the research results, OEE was increased by 5% in the horizontal machining center and 7% in the vertical machining center. In another study, Nallusamy and Muthamizhmaran [12] emphasized the development OEE of the autoclave process with the implementation of time and motion works. Low et al. [13] studied enhancing the setup process of injection molding machines through the developed setup improvement method. They employed overall performance effectiveness (OPE) to analyze the setup development. The results showed that OPE is a good way to observe the process. Garza-Reyes [14] proposed overall resource effectiveness (ORE) to further improve the OEE. Hedman et al. [15] aimed to determine critical inputs and potential pitfalls while operating automatic measurement of OEE. In the study, they found OEE to be 65%. In addition, almost 50% of recorded OEE losses could not be categorized. Azizi [16] proposed OEE as an indicator to determine equipment efficiency and, with the work done, it has been by improved 6.49%. Puvanasvaran et al. [17] employed Maynard’s Operation Sequencing Technique (MOST) in order to analyze the percentage development contributed to the OEE. A similar study was performed by the authors [18,19]. It is possible to extend studies conducted by Wolniak et al. [20], Wan et al. [21], and Salonitis and Kolios [22], who applied numerous tools in manufacturing, process, and service industries. Techniques are extensively used for improving the performance and effectiveness of numerous processes highlighted in the industry. The implementation of the combination of tools, techniques, and philosophies were methodically analyzed, investigated, and implemented by numerous investigators to maintain and sustain the processes by optimum use of resources during operation [12,14]. Yun et al. [23] discussed the entrance of new technology in market. In their work, they discussed the new channels and opportunities helpful in growth of open market. Yun et al. [24] also discussed the sustainability conditions of open innovation: dynamic growth of Alibaba from SME to large enterprise. In another work of Yun et al. [25], the culture about the open innovation dynamics has been discussed. Munir et al. [26] studied the open innovation tools in Sony mobile industry. Enkel et al. [27] discussed the open R&D and open innovation phenomena in an industry. Considering the literature information mentioned above, the present study proposed a new basis to increase the performance of an automotive manufacturing industry considered as micro, small, and medium enterprises (MSME). This paper demonstrates the effective utilization of Pareto analysis (PA), fishbone diagram (FBD), and overall equipment effectiveness (OEE) to mitigate the problems, which further spreads to increase the performance of the automotive industry. This study connects to essential information about collecting and analyzing the data in the industry. The results were thoroughly instructed and implemented in the industry. Practitioners must be educated with the use and understanding of tools used to increase the effectiveness of any industry. The present study contributes not only to the terms of improving the effectiveness but also to create an impact on sustainability. This paper mitigates the losses by using optimized machining attributes on the machine. The machining attributes contribute more to improving the availability (less machine failure due to rated condition), performance (more material removal rate, less machining time, and better speed rating), and quality (less rejection and rework). It also helps to lessen the energy requirements during machining, failure time, and repair time. The objective of this research is to (I) surge productivity, (II) surge equipment life by increase responsiveness of the need for maintenance, and (III) decline cost. Outcomes of these research objectives are to J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 4 of 23

J. Open Innov. Technol. Mark. Complex. 2021energy, 7, 7 requirements during machining, failure time, and repair time. The objective of4 of this 21 research is to (I) surge productivity, (II) surge equipment life by increase responsiveness of the need for maintenance, and (III) decline cost. Outcomes of these research objectives are to (I) conquer competitive edge, (II) surge turnover, (III) recognize equipment propri- (I) conquer competitive edge, (II) surge turnover, (III) recognize equipment proprietorship, andetorship, (IV) condense and (IV) overheads.condense overheads. TheThe studystudy isis divideddivided intointo different different sections sections as as follows. follows. TheThe researchresearch methodology methodology adoptedadopted duringduring thisthis studystudy isis presentedpresented inin Section Section2 .2. Section Sectio3n presents3 presents the the analyses analyses and and discussiondiscussion withwith ParetoPareto analysis,analysis, ﬁshbonefishbone diagram,diagram, andand overalloverall equipmentequipment effectiveness.effectiveness. TheThe conclusion conclusion is is presented presented in in Section Section4 .4.

2.2. MaterialsMaterials andand MethodsMethods TheThe presentpresent studystudy isis nurturednurtured withwith aa combination combination ofof ParetoPareto analysis analysis andand ﬁshbone fishbone diagramdiagram conceptconcept inin thethe industry.industry. Overall Overall equipment equipment effectiveness effectiveness measures measures existing existing and and laterlater performance performance within within the the industry industry and and the datathe data was collectedwas collected on the on occurrence the occurrence of losses of arisen,losses possiblearisen, possible causes, production,causes, production, scrap, and scra downtimep, and downtime for one month for one in month the automotive in the au- componentstomotive components manufacturing manufacturing industry. The industry. data is collectedThe data from is collected the industry from and the itindustry relates toand the it unsatisfactory relates to the performanceunsatisfactory of perfor the manufacturingmance of the premise.manufacturing The numerous premise. reasonsThe nu- whichmerous reduce reasons the which performance reduce of the manufacturing performance premisesof manufacturing are inappropriate premises maintenance, are inappro- poorpriate selection maintenance, of tool poor material, selection non-optimized of tool material, machining non-optimized attributes, andmachining setup time. attributes, This methodologyand setup time. helps This in methodology mitigate all these helps reasons in mitigate in a well-organizedall these reasons way in a towell-organized improve the performanceway to improve of the the industry. performance The of industry the indust wasry. visited The industry several timeswas visited for the several prescribed times periodfor the andprescribed observation period was and recorded observation for the was working recorded culture for the of working an operator, culture working of an op- of maintenance,erator, working production, of maintenance, and quality production, personals. and quality Figure1 personals. demonstrates Figure the 1 ﬂowchartdemonstrates of thethe research flowchart methodology of the research plan method used inology this study.plan used in this study.

FigureFigure 1. 1.Flowchart Flowchart of of the the research research methodology methodology plan plan used used in in this this work. work. J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 5 of 21

The research method adopted during this investigation not only focuses on performance improvement but tries to deliver the same information among the operator working in the industry. The existing OEE was evaluated and compared; if it needed improvement, then Pareto analysis and ﬁshbone diagram analysis were carried out. All the losses were mitigated through various strategies, tools, and techniques. OEE was re-evaluated and matched with the performance. If it was found okay, then changes are acceptable; otherwise, it was necessary to review the techniques and tools to improve the OEE. First, a familiarity about the method/techniques was discussed thoroughly among planning and maintenance teams to clear any misinterpretation that arose during observation and data collection. The observation for concerned machine tool procedure and other activities (planned shutdown time, unplanned downtime, scrap, breakdown) was carefully collected and investigated. The techniques like pro-active maintenance schedule, 5S approach in workstation, and autonomous maintenance approach shift the paradigm of an operator from “You to We.” This involves the use of cutting tools as recommended by either the manufacturer or machine data handbook, regular training and monitoring of the process and persons employed in production, and initiating industry-institute interface (3 I approach) for healthier utilization of resources within and around the industry. The results were analyzed after implementation and convinced the employees to follow the improved methods and technologies in the industry. The objective of this research is to (I) surge productivity, (II) surge equipment life by increase responsiveness of the need for maintenance, and (III) decline cost. Outcomes of these research objectives are to (I) conquer competitive edge, (II) surge turnover, (III) recognize equipment proprietorship, and (IV) condense overheads.

Overall Equipment Effectiveness The machine availability was the only parameter for evaluating equipment performance in an earlier era [28,29]. This methodology was used for comparison at the same output and same downtime. There is a high probability for speed loss due to start back up and quality forfeiture in form of scrap and rework, results from unforeseen stoppage. All the losses must be accountable, which can influence the capacity to mark output within the specified limit. The improvement actions must be prioritized for effective, better integration of all the losses. Equipment overall performance has set to be a more important indicator for calculating the performance of any industry and can be investigated through overall equipment effectiveness. This methodology can assimilate numerous factors availability, quality, and speed loss, so increasingly used in industrial atmospheres to evaluate the performance by comparing the theoretical maximum output and the actual output of the machine. The man, material, and procedure also take active participation in evaluating the effectiveness of a manufacturing plant. The performance of equipment and allied processes can be enhanced through recognizing prospects that reveal great influence on the production floor. The sustainability and reliability achievement reflects the efforts of planning and maintenance department with the concept of performability. Overall equipment effectiveness does not only mean ensuring reliability but it should also ensure sustainability. The ecological impact must be considered at each stage of operation to achieve sustainability in any industrial activity to counter the scarcity of resources in the 21st century. Clean production and knowledge can be envisioned for maximizing the yield by deploying the approach of reducing, recycling, and reusing in industries for minimizing the influence of production activities on ecology, which is the goal of performability. Effective utilization of manufacturing operation can be effectively focused by the hierarchy sustained at various levels of OEE. The outcome of OEE allows the setting of benchmarks between different departments, machines, and operations within and around several industries. The useful and powerful individualities of OEE enables its use in easy monitoring and improving the efficacy of production line or machines. OEE is the multiplication of three important factors, namely, availability, performance, and quality loss. Figure2 demonstrates the perfect model for OEE used in further study. Figure2 J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 6 of 23

J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 6 of 21

Figure 2 demonstrates the perfect model for OEE used in further study. Figure 2 also shows various losses encountered during operation in industry and must properly be ad- dressedalso shows to alleviate various their losses effects encountered on the OEE. during The operation OEE can intrace industry total productive and must properlymainte- nancebe addressed implementation to alleviate in the their industry effects alon on theg with OEE. performance The OEE can measurement trace total productiveof the system.maintenance World-class implementation manufacturing in the industries industry have along more with than performance 85% OEE measurement and to become of the a membersystem. World-classof this elite class manufacturing is among the industries goals of haveevery more company. than 85% The OEE OEE and score to describes become a themember performance of this elite of industry class is among and is thecategorized goals of every into four company. levels: The (i) OEE score> 85% describes have excel- the lentperformance competitiveness; of industry (ii) 70% and < is OEE categorized < 85% considered into four levels: good manufacturing (i) OEE > 85% have facilities; excellent (iii) 60%competitiveness; < OEE < 70% (ii)fall 70%under < OEEintermediate < 85% considered facilities; goodand (iv) manufacturing OEE < 60% shows facilities; bad (iii)afford- 60% ability.< OEE < 70% fall under intermediate facilities; and (iv) OEE < 60% shows bad affordability.

FigureFigure 2. 2. OverallOverall equipment equipment effectiveness effectiveness (OEE) (OEE) model. model.

3.3. Results Results and and Discussion Discussion EveryEvery industry industry wants wants to to present present itself itself in in at at least least a a second second level level of of OEE OEE performance performance metrics.metrics. Table Table 1 displays the key terms for thethe calculation of OEE andand it has been observed thatthat OEE OEE and and TEEP TEEP scores scores of of 68.60 68.60 % % and and 61 61.45%.45% need need improvement improvement in in their their operation operation andand scheduling. scheduling. The The OEE OEE results results from from the thecombination combination of individual of individual parameters parameters that com- that prisescomprises losses losses at various at various stages. stages. These Theselosses lossesmust be must tackled be tackled properly properly so that soOEE that can OEE be improved.can be improved. In this section, In this losses section, were losses tracked were by tracked Paretoby analysis Pareto and analysis fishbone and diagram. ﬁshbone OEEdiagram. metrics OEE were metrics evaluated were to evaluated counter the to counterperformance the performance of an existing of set an of existing operations. set of Figureoperations. 2 reveals Figure the2 sevenreveals big the losses seven that big take losses active that contribution take active contribution in degrading in the degrading numer- icalthe value numerical of key value metrics of key like metrics OEE, AU, like an OEE,d TEEP AU, and(Figure TEEP 3). (FigureThese seven3). These big losses, seven namely,big losses, planned namely, shutdown, planned setup shutdown, downtime, setup unplanned downtime, downtime, unplanned minor downtime, stoppage, minor re- ducedstoppage, speed, reduced rework, speed, and rework,start-up, and need start-up, to be scrutinized need to be systematically. scrutinized systematically.

3.1. Pareto Analysis The Pareto analysis helps in scrutinizing these losses operatively and it can be ex- tended to make a ﬁshbone diagram for one of the major losses. The improvements were implemented internally and externally in the industry. Operational outcomes and economic prosperity are the basis of Pareto analysis, and the unevenness among these two vital parameters contribute to Pareto analysis. The 80/20 rule is another name for Pareto analysis. J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 7 of 21

Table 1. Key parameters of OEE.

No. Key Terms Symbol Formula Value Unit

1. Plant Operating Time PO No. of shift × Working Hours 1× 8 hrs. = 8hrs = 480 Min 2 Short Breaks @10 min This includes short breaks/meal 2. Planned Shutdown Time P = 201 Meal Break @ 30 Min S breaks/preventive maintenance schedule min = 30 Total = 50

Planned Production Plant Operating Time (PO)—Planned 3. PT 480 − 50 = 430 Min Time Shutdown Time (PS) Downtime arises due to tooling failures, unplanned maintenance, general 4. Down Time D 40 Min T breakdowns, equipment failure, setup/changeover, and material shortages

Plant Production Time (PT)—Down 5. Operative Time OT 430 − 40 = 390 Min Time Loss (DT) The time needed to achieve the product in 6. Ideal Cycle Time C 1 Min T a suitable time Total production in a single shift during 7. Total no. of Pieces N 330 Count planned production time 8. Minor Stoppages M Misfeed, jams, sensor failure, etc. 30 Min

9. Net Operating Time NT Operative Time-Minor stoppages 390 − 30 = 360 Min Efficient Net 10. E Ideal Cycle Time (C ) × Total Pieces (N) 1 × 330 = 330 Min Operating Time T T Total no of pieces which do not adhere 11. Rejected Pieces N 35 Count R with the specification Total no of Pieces (N)—Rejected Pieces 12. Good Unit G 330 − 35 = 295 Count (NR) Availability Operating Time (O )⁄Planned 13. Availability A T 390/430 = 90.70 % Production Time (PT) Performance [ ( )× ( )] [ × ] 14. Performance P Ideal Cycle Time CT Total Pieces N 1 330 = 84.62 % Operative Time(OT ) 390 Quality 15. Quality Q Good Units/Total Units 295/330 = 89.39 % Overall Equipment Efficiency Overall Equipment 90.70 × 84.62 × 89.39 16. OEE A ×P × Q % Efficiency = 68.60 Operating Time (O )⁄Plant Operating 17. Asset Utilization AU T 390/480= 81.25 % Time (PO) Total Effective 81.25 × 84.62 × 89.39 18. TEEP AU × P × Q % Equipment performance = 61.45

It is a column graph type diagram drawn from the collected data, and the graph differentiates between the vital factors and trivial ones. The priorities were fixed on the selected problem serially after data collection. The major factors were tackled, which were more responsible for a specific problem. The problems were recognized, categorized, and grouped based on their reoccurrence and anticipated in form of a percentage. The abscissa represents factors arranged in descending order and vertex as percentage contribution. The graph shows its importance in the system and emphasizes the vital area rather than the trivial one. Figure4 demonstrates the first level Pareto analysis of the various losses J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 8 of 21

in the system. Draw a horizontal line across the 80% and draw a vertical line through its intersection on the abscissa. The area excluding 80% intersection attracts more to deal with these big losses in an effective manner. The chart reveals that reject/rework and minor stoppage along with speed loss must be properly monitored and needs to be thoroughly analyzed. The planned downtime is considered to be one of the seven losses and needs to J. Open Innov. Technol. Mark. Complex.be 2021 minimized, 7, x FOR PEER so thatREVIEW planned production time can be increased. The planned downtime8 of 23 comprises two short breaks and one meal break for the operator. This loss cannot directly take contribution to affect speed loss and quality loss.

100 90.7 89.39 84.62 81.25 80

68.6 61.45 60

% Value 40

0 Availability Performance Quality OEE AU TEEP Key metrices Figure 3. Performance value of key parameters. J. Open Innov. Technol. Mark.Figure Complex. 2021 3. Performance, 7, x FOR PEER REVIEW value of key parameters. 9 of 23

3.1. Pareto Analysis 60 The Pareto analysis helps in scrutinizing these losses operatively120 and it can be ex- tended to make a fishbone diagram Series 1 for one of the major losses. The improvements were Series 2 110 50implemented internally and externally in the industry. Operational outcomes and eco- 50 100 nomic prosperity are the basis of Pareto analysis,100 and the 100unevenness among these two vital parameters contribute to Pareto analys91 is. The 80/20 rule is another90 name for Pareto 40 analysis. 80 78 It is a35 column graph type diagram drawn from the collected data, and the graph dif- 70 ferentiates between the vital factors and trivial ones. The priorities were fixed on the se- 30 30 30 lected problem serially62 after data collection. The major factors were60 tackled, which were Series 1 more responsible for a specific problem.24 The problems were recognized,50 Series 2 categorized, and grouped based46 on their reoccurrence and anticipated in form of a percentage. The abscissa 20 40 represents factors arranged in descending order16 and vertex as percentage contribution. The graph shows its importance in the system and emphasizes the30 vital area rather than 27 10 the trivial one. Figure 4 demonstrates the first level Pareto analysis20 of the various losses in the system. Draw a horizontal line across the 80% and draw a vertical line through its 10 intersection on the abscissa. The area excluding 80% intersection attracts more to deal with 0 0 these big losses in an effective manner. The chart reveals that reject/rework0 and minor Planned down time Reject/Rework Minor stoppage Speed loss Unplanned down time Setup down time Startup and yield stoppage along with speed loss must be properly monitored and needs to be thoroughly Factors analyzed. The planned downtime is considered to be one of the seven losses and needs to be minimizedFigureFigure 4. First 4.so First Levelthat Level planned Pareto Pareto analysisanalysis production of ofbig big losses lossestime in OEE. can in OEE. be increased. The planned downtime comprisesThis two time short can bebreaks effectively and utilized one meal for performing break for the the scheduled operator maintenance. This loss activ- cannot directly take Thiscontributionities so time that canunplanned to be affect effectively time speed can be loss utilized inevitably and quality for cut performingdown loss. to some extent. the scheduled The further study maintenance ac- tivitiesput so more that emphasis unplanned on the time remaining can be three inevitably losses reject/rework, cut down minor to some stoppage, extent. and The further studyspeed put moreloss. emphasis on the remaining three losses reject/rework, minor stoppage, and speed loss. 3.2. Fish Bone Diagram (FBD) Analysis The prime objective was to make a broad understanding of factors that adversely affect the seven losses in the system. Based on the observation, these factors were characterized as technical subjects, people development subjects, and management subjects. These subjects were tackled properly by coordinate the technical subjects with a cross- functional team, people development subject with production area-based team, and management subject with managerial officials. The data was collected and an effective management tool was used to present this data efficiently. Fishbone diagram (FBD) uses an illustrative representation of causes and their effects and can be a much effective tool for a specific case [30]. The FBD shows its usefulness due to graphical appearance, which makes this tool highly effective for analyzing the production problem. If there is a cause, then the effect must be present within the system and vice versa. The diagram with suitable branches and sub-branches (twiglets) effectively shows their relation. Fishbone diagram needs to be drawn according to logic and follow the steps listed below:

1. The problem that was analyzed must be put into the right side of the fishbone diagram, sketch the skeleton with right side pointed arrow. 2. The effective causes of the problem, e.g., method, material, man, environment, and machine, are categorized into the main fishbone. 3. The main causes as mentioned in the second step need to be excavated thoroughly. The consequent causes are treated as middle fishbone and one cause represents one fishbone only. J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 9 of 21

3.2. Fish Bone Diagram (FBD) Analysis The prime objective was to make a broad understanding of factors that adversely affect the seven losses in the system. Based on the observation, these factors were characterized as technical subjects, people development subjects, and management subjects. These subjects were tackled properly by coordinate the technical subjects with a cross-functional team, people development subject with production area-based team, and management subject with managerial officials. The data was collected and an effective management tool was used to present this data efficiently. Fishbone diagram (FBD) uses an illustrative representation of causes and their effects and can be a much effective tool for a specific case [30]. The FBD shows its usefulness due to graphical appearance, which makes this tool highly effective for analyzing the production problem. If there is a cause, then the effect must be present within the system and vice versa. The diagram with suitable branches and sub-branches (twiglets) effectively shows their relation. Fishbone diagram needs to be drawn according to logic and follow the steps listed below: 1. The problem that was analyzed must be put into the right side of the fishbone diagram, sketch the skeleton with right side pointed arrow. 2. The effective causes of the problem, e.g., method, material, man, environment, and machine, are categorized into the main fishbone. 3. The main causes as mentioned in the second step need to be excavated thoroughly.

J. Open Innov. Technol. Mark. Complex.The 2021, 7 consequent, x FOR PEER REVIEW causes are treated as middle fishbone and one cause 10 of represents 23 one fishbone only. 4. The cause is further expanded until it reaches its maximum. The numerous branches 4.can The be drawcause is laterallyfurther expanded on the until skeleton it reaches through its maximum. middle The andnumerous small fishbone. Use an appropriatebranches can name be draw and laterally place withon the arrows.skeleton through middle and small fishbone. 5. ThisUse complete an appropriate step-by-step name and procedureplace with arrows. is called FBD as it looks like a spiky fishbone. The5. This fishbone complete diagram step-by-step for procedure the losses is ascalled interpreted FBD as it looks from like Pareto a spiky analysisfishbone. was drawn and explained.The fishbone Rework, diagram speed for the loss, losses and as minor interpreted stoppage from Pareto were analysis taken was into drawn consideration for FBD.and Figures explained.5–7 demonstrate Rework, speed loss, the and various minor causesstoppage associated were taken into with consideration these losses for and, hence, FBD wasFBD. Figures successfully 5–7 demonstrate drawn the by various adopting causes the associated above-listed with these procedure. losses and, hence, The performance was enhancedFBD was successfully by considering drawn by certain adopting causes, the above-listed and the procedure. source of The individual performance problems was was enhanced by considering certain causes, and the source of individual problems was systematicallysystematically analyzed analyzed throughthrough the the 5—why 5—why technique. technique.

FigureFigure 5. Fishbone5. Fishbone diagramdiagram for for rework/reject. rework/reject. J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 10 of 21 J.J. OpenOpen Innov.Innov. Technol.Technol. Mark.Mark. Complex.Complex. 20212021,, 77,, xx FORFOR PEERPEER REVIEWREVIEW 11 11 ofof 2323

FigureFigureFigure 6. 6.6.Fishbone FishboneFishbone diagramdiagram forfor for speedspeed speed loss.loss. loss.

FigureFigureFigure 7. 7.7.Fishbone FishboneFishbone diagramdiagram forfor for aa minor aminor minor stoppage.stoppage. stoppage.

FiguresFigures5– 75–7 reveal reveal that that thethe major major losses losses result result from from 5M and 5M comprise and comprise of numerous of numerous causes,causes,causes, which whichwhich decrease decreasedecrease thethethe timetime availableavailable available forfor for thethe theplannedplanned planned productionproduction production time.time. TheThe time. reappear-reappear- The reappear- anceanceance can cancan be bebe diminished diminisheddiminished by by properproper proper convergingconverging converging onon thethe on FBD.FBD. the FBD.FBDFBD analysisanalysis FBD analysis helpshelps aa lotlot helps inin a lot in lowering the losses. Industries fail to meet the demand even running 24/7. The steady loweringlowering the the losses. losses. IndustriesIndustries fail fail to to m meeteet the the demand demand even evenrunning running 24/7. The 24/7. steady The steady production level can be maintained by reducing these various causes, which leads to un- production level can be maintained by reducing these various causes, which leads to wanted stoppage during production. The 2nd2nd levellevel ParetoPareto analysisanalysis forfor majormajor causescauses waswas unwanted stoppage during production. The 2nd level Pareto analysis for major causes was framed as shown in Figure8 and demonstrates the higher percentage of common causes for speed loss, minor stoppages, and reject/rework. The chart reveals that tooling failure, unplanned maintenance, process parameter, and improper training fall under 80% and need to be addressed properly to alleviate the different losses. These four major issues resolve many issues that directly or indirectly affect the performability of an industry. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 12 of 23

J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 11 of 21 framed as shown in Figure 8 and demonstrates the higher percentage of common causes for speed loss, minor stoppages, and reject/rework.

18 120 Series 1 16 110 16 Series 2 100 100 14 96 93 90 86 12 80 11 77 70 10 9 64 60 8 Series 1 7 50 Series 2 48 6 40 5 4 30 4 29 20 2 2 2 10 0 0 Tooling failure Unplanned maintenance Process parameter Improrer training Properties Non-availability of material Composition Low skill Factors

Figure 8. Second Level Pareto analysis for commoncommon causes.causes.

3.3. OEEThe Improvementchart reveals Practices that tooling failure, unplanned maintenance, process parameter, 3.3.1.and improper Tooling Failuretraining fall under 80% and need to be addressed properly to alleviate the differentThis losses. paper These reported four the major study issues of the resolv automotivee many issues industry. that Threedirectly 8-hr or shiftsindirectly are scheduledaffect the performability with several machines.of an industry. In this work, machine number 20 was selected for a comprehensive study. The stepwise detailed analysis revealed that numerous causes participate3.3. OEE Improvement in poor performance Practices of operations. The tooling failure contributes further to reducing3.3.1. Tooling the plannedFailure production time and occurs for various causes [31–34]. The tooling consistsThis of paper a cutting reported tool the and study other of accessories. the automotive The industry. study shows Three that 8-hr frequent shifts are tooling sched- failureuled with adversely several affects machines. speed In loss, this minorwork, stoppages,machine number and reject/rework 20 was selected and for consequently a compre- hashensive an effect study. on The the performancestepwise detailed of the analysis industry. revealed An operator that numerous must verify causes the condition participate of thein poor cutting performance tool after regular of operations. intervals The of time tooling and, failure if needed, contributes the tool mustfurther be to either reducing replaced the orplanned sharpened production to resume time with and the occurs operations. for various These causes regular [31–34]. stops duringThe tooling the process consists create of a unplannedcutting tool timeand other loss in accessories. form of tool The failure, study increased shows that downtime, frequent tooling and further failure diminished adversely availabilityaffects speed of loss, the system;minor stoppages, creates minor and stoppagereject/rework and and speed consequently loss in the form has an of effect reduced on capacity and results shrunk in performance of the system; and creates reject/rework that the performance of the industry. An operator must verify the condition of the cutting tool results from faded cutting edges during operation in the form of poor-quality products after regular intervals of time and, if needed, the tool must be either replaced or sharpened and, hence, the quality rating is hampered. During interaction with the shop ﬂoor staff, it to resume with the operations. These regular stops during the process create unplanned was concluded that the solid cutting tools selected do not adhere with the recommendation time loss in form of tool failure, increased downtime, and further diminished availability of the manufacturer catalogue and are inappropriate with the workpiece material. The of the system; creates minor stoppage and speed loss in the form of reduced capacity and condition of the solid cutting tool is inspected by the operator to check its usability within results shrunk in performance of the system; and creates reject/rework that results from short time intervals. The worn-out tool needs to be ground again to resume the operation faded cutting edges during operation in the form of poor-quality products and, hence, the and sometimes the tool is not to be ground as per the speciﬁed tool geometry, which causes quality rating is hampered. During interaction with the shop floor staff, it was concluded severe surface defects. The higher authorities were communicated with suggestions as shown in Figure9. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 13 of 23

that the solid cutting tools selected do not adhere with the recommendation of the manufacturer catalogue and are inappropriate with the workpiece material. The condition of the solid cutting tool is inspected by the operator to check its usability within short time intervals. The worn-out tool needs to be ground again to resume the operation and some-

J. Open Innov. Technol. Mark. Complex.times2021, 7 ,the 7 tool is not to be ground as per the specified tool geometry, which causes severe12 of 21 surface defects. The higher authorities were communicated with suggestions as shown in Figure 9.

Figure 9. Suggestion to mitigate tooling failure.

3.3.2. Unplanned Unplanned Maintenance Maintenance Unplanned maintenance maintenance causes unadorned unadorned problems problems in in the the system, system, increased increased down- down- time,time, hampered hampered production production activities, activities, redu reducedced speed loss, minor stoppage, and reduced quality rate due to sudden breakdown on th thee machine tool. The The manufacturing manufacturing industries performance depends upon machine tools, and failure of these can put adverse effects on fulfillingfulfilling customercustomer demand. demand. The The failure failure also also creates creates ambiguities ambiguities on the on shop the shop floor andfloor hence and henceobstructs obstructs their efficiency their efficiency and creates and morecreates monetary more monetary deficits. Manufacturingdeficits. Manufacturing systems heart sys- temsincludes heart machine includes tools machine and needs tools and to maintain needs to these maintain tools these efficiently tools efficiently for healthy for breathing healthy breathingof the system. of the Therefore, system. Therefore, planned maintenance planned maintenance or proactive or proactive maintenance maintenance strategies strat- must egiesbe adopted must be to adopted prevent suchto prevent uncertainties such uncert in theainties system. in the Deficiencies system. Deficiencies during preventive during preventivemaintenance maintenance result in corrective result in maintenance, corrective maintenance, which is to bring which a piece is to of bring equipment a piece to itsof equipmentoriginal order. to its Unplanned original order. maintenance Unplanned also maintenance causes corrective also maintenancecauses corrective and needsmainte- to nancestop the and production needs to stop activities the production until the equipment activities returns until the to equipment its operational returns state. to Therefore, its oper- ationalcorrective state. maintenance Therefore, andcorrective preventive maintena maintenancence and needpreventive to be optimized maintenance for aneed reduction to be optimizedin downtime for and a reduction the same in has downtime been suggested and the and same discussed has been with suggested the management and discussed team. with Correctivethe management maintenance team. downtime includes three basic modules as listed and ex- plainedCorrective in Table 2maintenance. The corrective downtime maintenance includes efficacy three increases basic modules by adopting as listed strategies and ex- in plainedthe plant. in TheTable strategies 2. The corrective follow in themaintenanc industrye were efficacy explained increases as follows:by adopting strategies in1. theImprove plant. The interchangeability strategies follow: This in the concept industry is useful were in explained lowering as maintenance follows: time; the 1. Improveinclusion interchangeability of interchangeability: This concept during replacingis useful in and lowering removing maintenance parts consumes time; lessthe time and further extends planned production time. inclusion of interchangeability during replacing and removing parts consumes less 2. Improve fault acknowledgement, position, isolation: These three main activities consume timethe mostand further time in extends the industry. planned Faults production can be time. timely acknowledged and positioned 2. Improvethrough fault effective acknowledgemen maintenancet, position, procedure isolation: and well-trained These three personnel main activities employed consume in the industry. Effective training helps to diagnose and locate the fault through minimal the most time in the industry. Faults can be timely acknowledged and positioned efforts within the system. Vibration monitoring, oil particle analysis, and thermal throughimaging effective are some maintenance of the approaches procedure by which and well-trained faults can be personnel easily positioned employed and in theisolated. industry. An effectiveEffective troubleshootingtraining helps to procedure diagnose easilyand locate monitors the fault and recognizesthrough mini- the malfault. efforts The indisputablewithin the system. fault isolationVibration provides monitoring, more oil accuracy particle inanalysis, the time. and thermal 3. Human factors: The ergonomically designed components help to mitigate the corrective imagingmaintenance are some time. of The the various approaches components, by which pointers, faults can and be dials easily must positioned be arranged and isolated.ergonomically An effective on the troubleshooting machine as per proc theiredure size, easily shape, monitors and weight and criterion.recognizes This the fault.practice The reduces indisputable efforts fault as well isolation as time provides to convert more failure accuracy state in into the operational time. state within minimal time. 4. Use redundancy: The redundancy in the system will reduce the load on the production line in case of breakdown or failure in the line. The redundant components can be exchanged any time for the period of failure of the specific component for maintaining continuity in the system. Even though whole maintenance may not be affected, the equipment downtime decreases appreciably. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 14 of 23

3. Human factors: The ergonomically designed components help to mitigate the corrective maintenance time. The various components, pointers, and dials must be arranged ergonomically on the machine as per their size, shape, and weight criterion. This practice reduces efforts as well as time to convert failure state into operational state within minimal time. 4. Use redundancy: The redundancy in the system will reduce the load on the production line in case of breakdown or failure in the line. The redundant components can be exchanged any time for the period of failure of the specific component for maintain- J. Open Innov. Technol. Mark. Complex. 2021 7 , ing, 7 continuity in the system. Even though whole maintenance may not be affected,13 of 21 the equipment downtime decreases appreciably.

Table 2.TableCorrective 2. Corrective maintenance maintenance downtime downtime modules. modules.

AdministrativeAdministrativeandLogisticTime: and Logistic Time: Time takenTime for taken implementing for implementing decision decision through through administrative administrative department department and provide the same without any hinderence. and provide the same without any hinderence. CorrectiveActive RepairActive RepairTime: Time: Corrective Time taken to convert the failure state into operational state. This will MaintenanceTime taken to convert the failure state into operational state. This will de- MaintenanceDown Time depend upon checkout, preparation, fault correction, location, adjustment pend upon checkout, preparation, fault correction, location, adjustment Down Time and calibration, and spare item time. and calibration,Delay Time: and spare item time. Delay Time:The actual time taken by the system from the scheduled time referred as The actualdelay time time. taken by the system from the scheduled time referred as delay time. Preventive maintenance maintenance reduces reduces the the risk risk of ofseverity severity of ofbreakdow breakdown/failuren/failure in the in sys- the system.tem. The The effective effective maintenance maintenance schedule schedule lead leadss to to less less unplanned unplanned downtime. downtime. Preventive maintenance comprisescomprises various various elements elements as as shown shown in Figurein Figure 10. These10. These elements elements effectively effec- help the maintenance team to reduce the above-mentioned risks and failure. tively help the maintenance team to reduce the above-mentioned risks and failure.

•Inspection: Periodically inspecting and comparing actual physical, mechanical, and other conditions with standards. •Callibration: Correcting any inconsistency found while comparing with standards •Testing: Regular testing to maintain the equipment as per standards. •Adjustment: Continually making corrections as notified by the inspection team to achieve optimal effectiveness. •Servicing: Regularly cleaning, lubricating, and adjusting the equipment to prevent reoccurrence of failures. •Installation: Replacing the items regularly as per their limited life cycle and wear degradation pattern. Preventive Maintenance Preventive •Alignment: Align the replaced/repair items as per specified standards.

Figure 10. Elements of preventive maintenance.

Availability of necessary support support such such as as te testingsting instrument, instrument, tools, tools, a past a past database database of ofequipment, equipment, skilled skilled labor, labor, manufacturer manufacturer in index,dex, management management cooperation, cooperation, and manuals leads to an effectiveeffective preventivepreventive maintenancemaintenance program.program. First, the area must be chosen for initiation of maintenancemaintenance effort.effort. The maintenancemaintenance requirementsrequirements prioritized,prioritized, basedbased uponupon priorities of maintenance activities, were developed through daily and periodic inspections. Maintenance events occurrence were recorded and reviewed properly to make an effective daily and periodical maintenance plan. The ﬁnal plan for both the types was approved and executed at the shop ﬂoor level for desired results. The effective stepwise procedure helps to minimize the planned downtime for maintenance purposes.

3.3.3. Process Parameters The status of the process was measured concerning certain indicators and values. These values are known as process variable or process parameters. The parameters must be under uninterrupted control for effective use of equipment. The measured parameter always results in improved performance without affecting the system. The overall system performance can be acquired efﬁciently when process parameters are used to count machine reliability. As the process parameter changes, it will disturb the production rate, performance, and probability of failure of a given system. The inclusion of parameter per- J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 14 of 21

mits improved estimation of an overall performance rate. These parameters are influenced by workpiece formation and material. Therefore, proper selection of these parameters results in increased planned production time, reduced time, reductions in six big losses, and increased economy. Generally, three parameters i.e., cutting speed, depth of cut, and feed are considered for evaluation. Optimized machining attributes result in less tooling failure and consequential losses are reduced. If losses are reduced, then it leads to an increase in the effectiveness of the industry [35–39]. The cutting speed, expressed in meters per minute (m/min) or feet per minute (ft/min), is the path traveled by a point on the cutter. Literature reveals that using extremely slow cutting speed is unviable for production and extremely high cutting speed is unworkable for economical production [40]. The most viable cutting speed must be chosen for a workpiece tool interface without affecting performance and economy [41,42]. While selecting optimal cutting speed, feed (as per cutting tool strength and surface finish requirement) and depth of cut (machine tool, cutting tool and system requirement), all outcomes should be considered. Production efficiency comprises machining time, tool changing time, setup time, and costs associated with them. The proper selection of parameters results in optimal production rate (Pr) and production cost (Cp), as can be seen from Equations (1)–(4).

Nt Nb × Mt Tp = Ti + Mt + Tch , Tp = Ti + Mt + Tch (1) Nb Nb × T M T = T t ...; M = πdl/1000V f (2) edge ch T t c

Tp = Ti + Mt + Tedge (3) Cp = (K1 × Mt) + (K1 × Ti) + K1 × Tedge + (K2 × Mt/T) (4)

Nb × Mt Tp = Ti + Mt + Tch (5) Nb × T The machining economics helps to choose the process parameters to minimize the production unit time (Tp), which comprises of load/unload time (Ti), actual machining time (Mt), and the average time spent in changing insert tip (Tedge). Nb is the total components produce a batch, Nt is the total number of tools used. K1, K2 are man-machine hour rate ($/min) and the cost of consumable per cutting edge ($). The appropriate tool material (high-grade material), tool geometry (positive, neutral, and negative), tool inserts (Physical Vapor Deposition and Chemical Vapor Deposition), and optimal process parameter strongly influence the availability rate, performance rate, and quality rate. Equations (1)–(4) reveal that production time is dependent upon machining time, and further machining time shows the relation between cutting speed and feed. Equation (5) displays the tool life equation, where C, n, n1, and n2 are the constant depending upon the tool material. Also, C depends on the tool-workpiece material interface and helps to trace out the availability rate of the machine. Less tool life means more tool changing and less machine available, and vice versa. Repeated tool changing increases minor stoppages and reduces the speed, and so affects the performance rate of the industry. Abrupt breakage in the tool seriously damages the workpiece surface and sometimes the machine tool is also affected by these abrupt impacts, which leads to reject/rework, and hence affects the quality rate. The tool wear is highly influenced by cutting speed, feed, and depth of cut, and results in poor dimensional accuracy, process stability, and surface finish, causing reject/rework as shown in Figure 11. The same results were reported by Murat et al. in their scientific works [43]. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 16 of 23

(4) reveal that production time is dependent upon machining time, and further machining time shows the relation between cutting speed and feed. Equation (5) displays the tool life equation, where C, n, n1, and n2 are the constant depending upon the tool material. Also, C depends on the tool-workpiece material interface and helps to trace out the availability rate of the machine. Less tool life means more tool changing and less machine available, and vice versa. Repeated tool changing increases minor stoppages and reduces the speed, and so affects the performance rate of the industry. Abrupt breakage in the tool seriously damages the workpiece surface and sometimes the machine tool is also affected by these abrupt impacts, which leads to reject/rework, and hence affects the quality rate. The tool wear is highly influenced by cutting speed, feed, and depth of cut, and results in poor J. Open Innov. Technol. Mark. Complex.dimensional2021, 7, 7 accuracy, process stability, and surface finish, causing reject/rework15 of as 21 shown in Figure 11. The same results were reported by Murat et al. in their scientific works [43].

Figure 11. EffectEffect of tool wear on the machined surface.

3.3.4. Improper Training 3.3.4. Improper Training TrainingTraining greatly affects the overall performance of the industry. Third level Pareto analysisanalysis reveals reveals that that improper improper training training was was considered considered one one of the main causes as per the 80/2080/20 rule rule and, and, hence, hence, needs needs to to be be tackled tackled to to improve improve the the performance performance in in the the industry. industry. If thethe workforce workforce is is properly properly trained, trained, then then most most of of the the problems problems routinely routinely disappear disappear from the machinemachine area. area. A A skilled skilled workforce workforce understands understands the the effects effects of of following following non-standardized non-standardized procedureprocedure during during the the machining machining operation. operation. Th Thee motive motive of addressing of addressing tooling tooling failure, failure, unplannedunplanned maintenance, maintenance, and and proces processs parameter parameter is isto to mitigate mitigate th thee big big losses losses that that can can result result fromfrom the the unskilled unskilled worker. worker. Unskilled Unskilled workforce workforce needs needs to to undergo undergo training training to to fortify fortify their their skillsskills as as well well as as utilize utilize their their improved improved skills skills in inimproving improving thethe overall overall effectiveness effectiveness of the of industry.the industry. The Theeffect effect of these of these minor minor changes changes is observed is observed during during the the operation. operation. Labor Labor is reinforcedis reinforced with with the the training training of 5S of 5Sterminol terminologyogy and and autonomous autonomous maintenance maintenance in the in thein- dustryindustry to tokeep keep industry industry progressive progressive in innature. nature.

3.3.5.3.3.5. 5’S 5’S Methodology Methodology EveryEvery organization organization deals deals with with poor poor effectiven effectivenessess due due to to waste waste in in the the form of either defect,defect, waiting waiting time, time, superfluous superfluous motion, motion, surplus surplus inventory, inventory, extra processing, pointless conveyance,conveyance, and and unutilized unutilized talents. This This te techniquechnique helps helps to to incr increaseease performance by maintaining the workplace clean, reliable, well managed, and uncluttered. This technique not only recognizes five words but helps the organization to reduce wastage and losses. The industry faces too much-unplanned downtime due to cluttered organization. The 5’S methodology is the right technique to conquer cluttered organization. The shop floor scan cum diagnostic sheet was prepared and successfully communicated with management team for improvement in the industry, as demonstrated in Table3. The sheet rated five levels from L1 to L5. If more than four problems occur, then L1 is written in the sheet; three problems mean L2; two problems mean L3; 1 problem means L4; and zero problem means L5. J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 16 of 21

J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 18 of 23 J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 18 of 23 J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 18 of 23 Table 3. Shop ﬂoor scan cum diagnostic sheet. J.J. OpenOpen Innov.Innov. Technol.Technol. Mark.Mark. Complex.Complex. 20212021,, 77,, xx FORFOR PEERPEER REVIEWREVIEW 18 18 ofof 2323

Table 3. Shop floor scan cum diagnostic sheet. Rating Remarks Classification Table 3. Shop floorDescriptions scan cum diagnostic sheet. Table 3. Shop floor scan cum diagnostic sheet. RatingL1 L2 L3Remarks L4 L5 Classification TableTable 3.3. ShopShopDescriptions floorfloor scanscan cumcum diagnosticdiagnostic sheet.sheet. Rating Remarks Classification 1. DistinguishDescriptions between wanted and unwanted itemsL1 L2 RatingL3 L4 L5 Remarks Classification 1. Distinguish betweenDescriptions wanted and unwanted items L1 L2 L3 L4 L5 L1 L2 RatingRatingL3 L4 L5 RemarksRemarks ClassificationClassificationSEIRI 1. 2. UnwantedDistinguish Unwanted equipment, between equipment,DescriptionsDescriptions wanted tool, tool, other and otheritemsunwanted itemson the items onshop the shop floor. SEIRI 2.1. Distinguish between wanted and unwanted items L1L1 L2L2 L3L3 L4L4 L5L5 ORGANIZEORGANIZE floor.Unwanted equipment, tool, other items on the shop SEIRI 1.1.2. 3. DistinguishUnwantedDistinguish Purpose equipment, of betweenbetween the items, wantedwanted tool, frequency other andand unwanted unwanteditems of on use the itemsitems shop ORGANIZE(SORT)(SORT) 2. floor. A A ORGANIZESEIRISEIRI 3. PurposeUnwanted of theequipment, items, frequency tool, other of itemsuse on the shop (SORT) 4.Unwantedfloor. Unwanted equipment, items in tool, the staircase,other items corners. on the shop A ORGANIZE 2.4.2.3. Unwanted Purpose of itemsthe items, in the frequency staircase, ofcorners. use A ORGANIZE(SORT) 3. floor. Purposefloor. of the items, frequency of use (SORT) 5.4. 5. Unwanted Unwanted Unwanted itemsitems items onin thewalls on staircase, walls and information and corners. information board. board. AA (SORT) 3.4.3. Purpose UnwantedPurpose ofof theitemsthe items,items, in the frequencyfrequency staircase, ofof corners. useuse 6.5. Unwanted Unwanted inventoryitems on walls supplies and orinformation materials. board. 4.5.4. 6. Unwanted Unwanted Unwanted itemsitems inventory ininon thethe walls staircase,staircase, suppliesand information corners.corners. or materials. board. SEITON 7.6. A Unwanted place of everything inventory suppliesand everything or materials. in its place. 5.6.5. Unwanted Unwanted itemsitemsinventory onon wallswalls supplies andand informationorinformation materials. board. board. UNIFORMITSEITON 8.7. 7. Items A A place place are of not ofeverything everythingin order and andeverything everything in its place. in its place. SEITON 6.7.6. Unwanted AUnwanted place of everythinginventoryinventory suppliessupplies and everything oror materials.materials. in its place. UNIFORMITYSEITON (SET IN 8. Items are not in order UNIFORMITSEITON 9.7. 8. Workstations, A Items place of are everything not items inorder location and everything not demarcated in its place. B UNIFORMITYYSEITON (SET IN 7.8. A Items place are of not everything in order and everything in its place. ORDER) 10.9. CorrectWorkstations, items not items grouped location not demarcated B UNIFORMITY (SET IN 9.8. Workstations, Items are not in items order location not demarcated B (SETUNIFORMITORDER) IN ORDER) 8.10.9. ItemsCorrect Workstations, are items not in not order itemsgrouped location not demarcated B YORDER) (SET IN Y (SET IN 9.11.10.9. Workstations, QuantityCorrectWorkstations, items limits notitemsitems are grouped not locationlocation appropriate notnot demarcateddemarcated BB 10. Correct items not grouped ORDER)ORDER) 10.10.11. CorrectCorrect Quantity itemsitems limits notnot are groupedgrouped not appropriate 11. Quantity limits are not appropriate 12. 11. Cleaning Quantity and limits looking are ways not appropriateare not organized SEISO 11.12. QuantityCleaning limitsand looking are not ways appropriate are not organized SEISO 11.13. QuantityWorkplace limits area, are floor, not stairsappropriate are contaminated CLEANLINES 12. Cleaning and looking ways are not organized SEISO 13.12. Machine Workplace Cleaning tools, area, and equipment’s floor, looking stairs ways and are othercontaminated are not items organized are not CLEANLINESS (SHINE) 12.14.13.12. Cleaning WorkplaceCleaning andand area, lookinglooking floor, waysways stairs areare are notnot contaminated organizedorganized C CLEANLINESSEISOSEISO 13.clean.Machine Workplace tools, area, equipment’s floor, stairs and other are contaminated items are not S (SHINE) 13.13.14. WorkplaceMachine Workplace tools, area,area, equipment’s floor,floor, stairsstairs andareare contaminatedcontaminatedother items are not C CLEANLINESSCLEANLINESCLEANLINESS (SHINE) 15.14. Sanitaryclean. items are not easily assessable. C 14. Machineclean.MachineMachine tools,tools, tools, equipment’sequipment’s equipment’s andand otherother and other itemsitems are itemsare notnot are not clean. SS(SHINE) (SHINE)(SHINE) 14.16.14.15. Signage Sanitary and items board are notare easeitherily assessable.dirty or broken. CC C 15. clean. Sanitaryclean. items are not easily assessable. 17.16. 15. Relevant Signage Sanitary andissues items board are are not either easily dirty assessable. or broken. 15.16.15. Sanitary SignageSanitary anditemsitems board areare notnot are easeas eitherilyily assessable.assessable. dirty or broken. SEIKETSU 18.17. ImplementationRelevant issues of the first 3S 16.17.16. 16. SignageRelevant Signage Signage andand issues and boardboard board areare eithereither are either dirtydirty dirty oror broken.broken. or broken. STANDARDISEIKETSU 19.18. Standards Implementation are not of properly the first documented3S SEIKETSU 17.18.17. Relevant ImplementationRelevant issuesissues of the first 3S STANDARDIZE 19.17. Standards Relevant are issues not properly documented STANDARDISEIKETSU 20.18. Job, Implementation cleaning, and of another the first checklist 3S not framed SEIKETSUZE 18.19. Implementation Standards are not of properly the first 3Sdocumented (NORMALIZ 21.20. Part Job, recognitioncleaning, and is anotherpoor checklist not framed STANDARDISTANDARDISEIKETSUZE 19.20.19. 18. Standards Job,Standards Implementation cleaning, areare andnotnot properlyproperlyanother of the checklist firstdocumenteddocumented 3S not framed D (NORMALIZE) 21. Part recognition is poor STANDARDIZE(NORMALIZZE D ZEE) 20.21.20. 19. Job, PartJob, Standards cleaning, cleaning,recognition areandand is not another anotherpoor properly checklistchecklist documented notnot framedframed D (NORMALIZE)(NORMALIZ(NORMALIZE) 21. Part recognition is poor 21.22. PartItems recognition located in specifiedis poor limit D E) 20. Job, cleaning, and another checklist not framed D D E) 22. Items located in specified limit 22.21. Items Part located recognition in specified is poor limit 22. Items located in specified limit SHITSUK 22.23. ItemsAdhere located with rules in specified limit 22. Items located in specified limit DISCIPLINESHITSUK 24.23. WorkersAdhere with not undergone rules 5S training SHITSUK 23. Adhere with rules DISCIPLINE(SUSTAIN) 24.23. Workers Adhere not with undergone rules 5S training DISCIPLINESHITSUKSHITSUK 25.23. TheAdhere frequency with rules for not performing 5S in last week (SUSTAIN)SHITSUK 23.24. Adhere Workers with not rulesundergone 5S training E 26.25. How The frequency many jobs for not not updated performing as per 5S standard in last week DISCIPLINEDISCIPLINEDISCIPLINE(SUSTAIN) 25.24. 24. TheWorkers Workers frequency not not undergone for undergone not performing 5S training 5S training 5S in last week E 24.26. Workers How many not jobs undergone not updated 5S training as per standard E (SUSTAIN)(SUSTAIN)(SUSTAIN) 25.26.25. 25. The HowThe The frequencyfrequency many frequency jobs forfor not fornotlastnot updated performing notweekperforming performing that as per belongings 5S5S standard inin lastlast 5S in week weeknot last week E 27. EE 26. properly HowThe frequency many maintained jobs for not last updated week that as per belongings standard not 26.27. HowThe frequency many jobs for not last updated week that as per belongings standard not 27.26. properly How many maintained jobs not updated as per standard TheproperlyThe frequencyfrequency maintained forfor lastlast weekweek thatthat belongingsbelongings notnot 27.27. The frequency for last week that belongings not 3.3.6.27. Autonomousproperlyproperly maintainedmaintained Maintenance 3.3.6. Autonomousproperly maintained Maintenance 3.3.6.This Autonomous maintenance Maintenance is the first pillar of total productive maintenance strategy. As in- 3.3.6.This Autonomous maintenance Maintenance is the first pillar of total productive maintenance strategy. As in- 3.3.6.dustryThis Autonomous mostly maintenance suffers Maintenance from is the either first plannedpillar of downtimetotal productive or unplanned maintenance downtime, strategy. each As time industry mostly3.3.6. 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TheThe autonomousautonomous procedureprocedure isis demonstrateddemonstrated inin FigureFigure 12.12. J. Open Innov. Technol. Mark. Complex. 2021, 7, 7 17 of 21

J. Open Innov. Technol. Mark.through Complex. 2021 effective, 7, x FOR PEER repair REVIEW and management. The autonomous procedure is 19demonstrated of 23 in

Figure 12.

FigureFigure 12. Autonomous12. Autonomous maintenancemaintenance procedure. procedure.

3.4. Improved OEE 3.4. ImprovedFigure OEE 3 reveals that the overall equipment effectiveness of the machine was 68.6%. FigureThere were3 reveals a lot of thatscopes the to increase overall this equipment OEE for the improvement effectiveness of the of industry. the machine Efforts was 68.6%. There were made a lot through of scopes the toimplementation increase this of OEEan effective for the strategy improvement in the industry. of the Six industry. big Efforts losses adversely affect the effectiveness of industry, and these losses were thoroughly at- were madetempted through with the help the of implementation 1st, 2nd, and 3rd Pa ofreto an analysis effective and FBD. strategy The major in the causes industry. like Six big lossestooling adversely failure, affect unplanned the effectivenessmaintenance, proc ofess industry, parameter, andand improper these losses training were were thoroughly attemptedthoroughly with theanalyzed help and of 1st, effectively 2nd, and commu 3rdnicated Pareto with analysis the production and FBD. and The manage- major causes like toolingment failure, teams. unplanned The improved maintenance, data were apprehended process and parameter, improved OEE and was improper calculated trainingas were thoroughlylisted in analyzed Table 4. and effectively communicated with the production and management teams. The improvedTable data 4. Improved were apprehendedkey metrics. and improved OEE was calculated as listed in Table4. No. Key Terms Symbol Past Value Present Value Unit 1. Plant Operating Time PO 1 × 8 hrs. = 8 hrs = 480 1 × 8 hrs. = 8 hrs = 480 min Table 4. Improved key metrics. 2 Short Breaks @10 min = 20 2 Short Breaks @10 min = 20 No.2. Key TermsPlanned Shutdown SymbolTime PS 1 Meal Past Break Value @ 30 min = 30 1 Meal Break Present @ 30 min Value = 30 min Unit Total = 50 Total = 50 1. Plant3. Operating Planned Time Production Time PO PT 1 × 8 hrs.480 = − 8 50 hrs = 430 = 480 1 480× −8 50 hrs. = 430 =8 hrs = 480 min min 4. Down Time DT 2 Short Breaks @1040 min = 20 2 Short Breaks 20 @10 min =min 20 5. Operative Time OT 430 − 40 = 390 430 − 20 = 410 min 2. Planned Shutdown Time PS 1 Meal Break @ 30 min = 30 1 Meal Break @ 30 min = 30 min 6. Ideal Cycle Time CT Total =1 50 1Total = 50 min 7. Total no. of Pieces N 330 380 count 3. Planned Production Time P 480 − 50 = 430 480 − 50 = 430 min 8. Minor Stoppages T M 30 15 min 4.9. Down Time Net Operating TimeD T NT 39040 − 30 = 360 410 – 15 = 395 20 min min 10. Efficient Net Operating Time ET 1 × 330 = 330 1 × 380 = 380 min 5. Operative Time OT 430 − 40 = 390 430 − 20 = 410 min 11. Rejected Pieces NR 35 15 count 6.12. Ideal Cycle TimeGood Unit CT G 3301 − 35 = 295 380 − 15 = 365 1 count min 7. Total13. no. of Pieces Availability N A 390/430 330 = 90.70 410/430 = 95.30 380 % count [ × ] [ × ] 14. Performance P = 84.62 = 92.68 % 8. Minor Stoppages M 30 15 min 15. Quality Q 295/330 = 89.39 365/380 = 96.05 % 9. Net16. Operating Overall TimeEquipment Efficiency NT OEE 90.70390 × −84.6230 =× 360 89.39 = 68.60 95.30 × 92.68 410 × 96.05 – 15 == 39584.83 % min

10. Efﬁcient17. Net Operating Asset TimeUtilization ET AU 1 × 390/480330 = = 330 81.25 410/480= 1 × 85.41380 = 380 % min

11. Rejected Pieces NR 35 15 count 12. Good Unit G 330 − 35 = 295 380 − 15 = 365 count 13. Availability A 390/430 = 90.70 410/430 = 95.30 % 14. Performance P [1 × 330] [1 × 380] % 390 = 84.62 410 = 92.68 15. Quality Q 295/330 = 89.39 365/380 = 96.05 % 16. Overall Equipment Efﬁciency OEE 90.70 × 84.62 × 89.39 = 68.60 95.30 × 92.68 × 96.05 = 84.83 % 17. Asset Utilization AU 390/480 = 81.25 410/480= 85.41 % J. Open Innov. Technol.J. Open Mark. Innov. Complex. Technol. 2021 Mark., 7, Complex. x FOR PEER REVIEW7 20 of 23 2021, , 7 18 of 21

4. Conclusions 4. Conclusions The healthy strategies in the industry help to sustain effectiveness for qualitative and The healthy strategies in the industry help to sustain effectiveness for qualitative quantitative production, which leads to higher customer satisfaction. To ensure this, re- and quantitative production, which leads to higher customer satisfaction. To ensure this, searchers proposedresearchers a novel proposed approach a novelin this approach study for in increasing this study the for effectiveness increasing thein the effectiveness in industry. Therethe are industry. seven major There losses are seven present major in lossesthe industry present which in the adversely industry whichaffects adverselythe affects effectiveness theof machine effectiveness in any of industry. machine This in any approach industry. can This reduce approach these canlosses reduce and im- these losses and prove the quality,improve asset the utilization quality, asset (AU), utilization OEE, total (AU), effective OEE, total equipment effective performance equipment performance (TEEP), and productivity(TEEP), and of productivity the machine. of theThe machine. study exposes The study that Pareto exposes analysis that Pareto uncovers analysis uncovers all the losses alland the works losses on and the worksprinciple on theof 80/20 principle rule. of The 80/20 major rule. losses The were major thoroughly losses were thoroughly explored withexplored the help with of the the fishbone help of thediagram fishbone and diagramsolutions and were solutions implemented were implemented on the on the shop floor. shop floor. In the currentIn paper, the current the OEE paper, approach the OEE jointly approach with Pareto jointly analysis with Paretoand fishbone analysis di- and fishbone agram accordsdiagram superior accords control superior over the control production over theefficiency. production Planned efficiency. downtime, Planned re- downtime, ject/rework, minorreject/rework, stoppage, minor and speed stoppage, loss co andnsidered speed main loss causes considered through main Pareto causes anal- through Pareto ysis as presentedanalysis in Figure as presented 4. The losses in Figure reject/rework,4. The losses minor reject/rework, stoppage, minorspeed stoppage,loss, un- speed loss, planned downtime,unplanned and setup downtime, downtime and decreased setup downtime as demonstrated decreased by as Figure demonstrated 13. Perfor- by Figure 13. mance key metricsPerformance were remarkably key metrics improved were remarkably (refer to improvedFigure 14). (refer In other to Figure word, 14 key). In other word, metrics i.e., availability,key metrics performance, i.e., availability, quality, performance, OEE, asset quality, utilization, OEE, asset and utilization, total effective and total effective equipment performanceequipment performanceshowed improvements showed improvements by 4.6%, 8.06%, by 6.66%, 4.6%, 8.06%, 16.23%, 6.66%, 4.16%, 16.23%, and 4.16%, and 14.58%, respectively,14.58%, respectively,after successful after execution successful of executiontrilogy approach of trilogy in the approach industry. in theThe industry. The statistical tool,statistical condition tool, moni conditiontoring, and monitoring, other management and other managementtools can be used tools to can mitigate be used to mitigate the losses. In thesummary, losses. Inthe summary, approach theoffers approach a good offersopportunity a good for opportunity both researchers for both and researchers and small-mediumsmall-medium enterprises around enterprises the aroundworld theto analyze world to the analyze indicators the indicators of production of production losses, losses, performance,performance, and productivity and productivity in the in themanufacturing manufacturing industry. industry. Research Research efforts efforts proposed in proposed in thethe future future include include further further development of existingexisting assessmentassessment methods,methods, conducting con- hybrid ducting hybridanalysis analysis by by collaborating collaborating with with different different methods, methods, and and investigatinginvestigating moremore determining determining factors affecting key metrics in the manufacturing industry.

50 Before After

30 Minute 20

0 Planned down time Reject/rework Minor stoppage Speed loss Unplanned down time Setup down time Startup and yield Key terms

Figure 13. Comparison of Figureseven big 13. losses.Comparison of seven big losses. J. Open Innov. Technol.J. Open Mark. Innov. Complex. Technol. 2021 Mark., 7, Complex.x FOR PEER2021 ,REVIEW7, 7 21 of 23 19 of 21

100 Before 90 After

% value 40

0 Availability Performance Quality OEE AU TEEP

Key metrics Figure 14. Comparison of keyFigure metrics. 14. Comparison of key metrics.

Author Contributions: Conceptualization, A.T., K.N.S., and M.K.G.; methodology, A.T. and Author Contributions: Conceptualization, A.T., N.S.K., and M.K.G.; methodology, A.T. and M.K.G.; M.K.G.; software, M.K.G. and M.S.; validation, M.K.G., D.Y.P., and K.N.S.; formal analysis, A.T. software, M.K.G. and M.S.; validation, M.K.G., D.Y.P., and N.S.K.; formal analysis, A.T. and M.K.G.; and M.K.G.; investigation, A.T.; resources, M.K.G. and D.Y.P.; data curation, A.T. and K.N.S.; writ- investigation, A.T.; resources, M.K.G. and D.Y.P.; data curation, A.T. and N.S.K.; writing—original ing—original draft preparation, A.T.; writing—review and editing, A.T. and C.I.P.; visualization, draft preparation, A.T.; writing—review and editing, A.T. and C.I.P.; visualization, M.S. and M.K.G.; M.S. and M.K.G.; supervision, K.N.S.; project administration, K.N.S. All authors have read and supervision, N.S.K.; project administration, N.S.K. All authors have read and agreed to the published agreed to the published version of the manuscript. version of the manuscript. Funding: This research received no external funding. Funding: This research received no external funding. Data Availability Statement: The data presented in this study are openly available online. Data Availability Statement: The data presented in this study are openly available online. Conflicts of Interest: The authors declare no conflict of interest. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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