Data Acquisition Using Arrowhead Framework for Condition Based Maintenance of Industrial Equipment

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Data Acquisition Using Arrowhead Framework for Condition Based Maintenance of Industrial Equipment Data Acquisition using Arrowhead Framework for Condition Based Maintenance of Industrial Equipment Johan Jansson Högberg Computer Science and Engineering, master's level 2019 Luleå University of Technology Department of Computer Science, Electrical and Space Engineering ABSTRACT As Industry 4.0 and Internet of Things are established across factories and enterprises, the interest for learning more about these concepts and the possibilities they provide for condition based maintenance is expressed by a factory in Sweden. By addressing the aspects of Internet of Things and Industry 4.0, a system for performing data acquisition from sensors in an industrial environment is developed using Arrowhead Framework. This framework is evaluated around its suitability for this kind of application, and re- garding what the framework may provide to the factory compared to other solutions and systems. A solution featuring a system based on Arrowhead Framework is developed, implemented, and briefly tested. The system is successful in performing data acquisition, and Arrowhead Framework is considered a viable option that may be used to provide a system tailored for different purposes, presumed that the factory is prepared to allocate resources on developing a solution around it. iii PREFACE This thesis work has been a challenging, but yet greatly rewarding experience for me. I am grateful to have had the possibility to perform my thesis work within this industry, and being able to work with all the people involved here. I have been taught many things and experiences, which I am glad to be able to bring with me to future workplaces. I would like to thank my supervisor Ulf Bodin at Lule˚aUniversity of Technology and company supervisor Isak Grimholm for providing me with the guidance needed to realise this thesis work. I would like to thank Jens Aslin˚ for the great cooperation we have had, as well as the guys at IFM and the employees of the IT department at the factory who have supported me by providing tips, help and material needed for this work. Last but not least, I would like to thank PhD student Cristina Paniagua at Lule˚aUniversity of Technology for helping me solve problems I have encountered while working with Arrowhead Framework. Johan Jansson H¨ogberg v CONTENTS Chapter 1 { Introduction 3 1.1 Background . 3 1.2 Motivation . 4 1.3 Problem Definition . 4 1.3.1 System Requirements . 4 1.3.2 Topic Related Questions . 5 1.4 Delimitations . 5 1.5 Related Work . 6 1.5.1 Components and services of Industry 4.0 and IoT . 6 1.5.2 Usage of Arrowhead Framework in similar applications. 6 1.5.3 Similar project previously held at the factory . 6 Chapter 2 { Method 9 2.1 Method . 9 2.1.1 Research Methodology . 9 2.1.2 Evaluation . 10 Chapter 3 { Theory 13 3.1 Industry 4.0 . 13 3.2 Internet of Things . 13 3.3 Cloud- and fog computing . 14 3.4 Industrial automation systems . 14 3.4.1 ISA-95 . 14 3.4.2 RAMI 4.0 . 16 3.5 OPC and OPC-UA . 16 3.6 Service-oriented architectures . 18 3.7 Arrowhead Framework . 18 3.7.1 Concept . 19 3.7.2 Core systems . 19 3.7.3 Compliance and maturity levels . 22 Chapter 4 { Plant System 25 4.1 Transportation Buffer . 25 4.1.1 Transportation Cart . 25 4.1.2 Network structure . 27 4.2 Alternative Proof of Concept . 27 Chapter 5 { Solution 29 5.1 Solution overview . 29 5.2 Sensors . 30 5.2.1 IO-Link sensors . 31 5.2.2 Vibration sensors and IFM VSE100 Diagnostic electronic . 32 5.3 Arrowhead Framework components . 32 5.4 Connectivity towards networks and internet . 33 5.5 Microsoft Azure . 34 5.6 ThingWorx . 34 Chapter 6 { Results, Evaluation and Future work 37 6.1 Resulting implementation . 37 6.2 Evaluation and discussion . 41 6.3 Future work . 43 6.3.1 Sensors and framework components . 44 6.3.2 Cloud services and analysis . 44 Appendix A{ Tables and Graphs 45 viii Abbreviations & Acronyms AHF . Arrowhead Framework API . Application Programming Interface BU3 . The sequential buffer at the factory CBM . Condition-Based Monitoring ERP . Enterprise Resource Planning IIoT . Industrial Internet of Things IoT . Internet of Things IR . Infrared MES . Manufacturing Execution System OPC . Open Platform Communications OPC-UA . Open Platform Communications Unified Architecture PLC . Programmable Logic Controller PoC . Proof of Concept RAMI4.0 . Reference Architecture Model Industrie 4.0 SCADA . Supervisory Control and Data Acquisition SOA . Service Oriented Architecture 1 CHAPTER 1 Introduction 1.1 Background Industry 4.0 and Internet of Things are two popular topics regarding the development of and evolution within industries today. The industrial digitization that is occurring enables manufacturers to more easily observe and interact with machines and manufac- turing equipment, in favour for optimizing and increasing production. One area that has benefited from this is the utilization of condition-based maintenance (CBM), where equipment is maintained with regard to its condition, rather than being maintained on a interval-basis regardless of condition. This thesis focuses on a factory that is looking to modernize and take part of the benefits from condition-based maintenance. At this factory, equipment in a certain pro- duction line is maintained on a pre-planned interval-based maintenance routine. During each maintenance occasion, the equipment is inspected manually and treated upon judge- ments from visual inspection. As the inspections are carried out by hand, humans need to physically enter the area of the equipment. Due to safety regulations, any affected production equipment may not be in operation when inspections occur. Consequently, inspections are often scheduled to occur mainly during nights and weekends, outside pro- duction hours. This in turn may lead to high operational costs in terms of expensive maintenance efforts, unforeseen repairs if malfunctions arise between maintenance occa- sions, and in case production is halted during active hours; overtime production in order to cover for lost production time. Another effect that follows from this is a larger amount of staffing as a result of installing a higher capacity to cover the maintenance and repair needs. There is also a risk of a poorer quality outcome as a result of equipment malfunc- tioning, causing direct or indirect quality impacts on the product in case equipment is not maintained properly. Apart from production impacts, malfunctions also increase the risk of injuries to persons. To be able to continue the production in an effective and competitive way in the future, the factory wishes to modernize and increase the efficiency of the maintenance, as well 3 4 Introduction as taking steps towards Industry 4.0. 1.2 Motivation The factory wishes to advance from the interval-based maintenance that is used today and establish a condition-based maintenance routine for the equipment, as well as explore the area of Industry 4.0 and the possibilities it provides. To enable condition-based maintenance, the idea is to with the use of sensors measure parameters of the equipment which are likely to provide information that can be correlated to wear of the parts in the equipment. By storing the sensed data for the different parameters a model may be created from it. This model may be used for determining the condition of the equipment using real-time data, and finally establish a condition-based maintenance routine. 1.3 Problem Definition The goal of this master thesis is to provide and implement a solution using Arrowhead Framework, a service-oriented software architecture developed for industrial automation. The solution shall enable data collection from sensors on legacy equipment, and store the data in a location it can be reached for processing, visualization, and analysis. A visualization platform will visualize stored and real-time sensor data. The solution shall utilize Industry 4.0 concepts as a way to demonstrate its possibilities for future interest. The targeted equipment the solution is developed for is a transportation cart in a large sequential buffer, which transports, stores, and sorts the manufactured goods between assembly lines. Furthermore, the factory has engaged a project to rebuild this sequential buffer, making it a suitable target as it more easily may be adapted to be able to utilize the solution produced from this thesis, if desired. The reason behind choosing Arrowhead Framework for this purpose is purely out of interest as it is a newly developed framework and the product of a large EU project involving many partners, including Lule˚aUni- versity of Technology. More of this in section 3.7. By performing this implementation, Arrowhead Framework is investigated and demonstrated regarding its usefulness for the factory and suitability for this type of application. 1.3.1 System Requirements Besides the general goals, there are some specifications and requests regarding the system that the factory wishes to meet. The system shall: • Be a generic IoT-platform. • Be scalable and flexible in such way that additional hardware may be added to the system to expand its physical size and area of operation, and able to have hardware replaced or upgraded with other hardware. 1.4. Delimitations 5 • Be compliant with any sensors and adjoining systems. • Refine and identify the data connecting it to events in the real system. • Be compliant with legacy-equipment. These requests are established as the factory do not want the system to be restricted for usage with only specific systems and suppliers. This strengthens the motivation for using Arrowhead Framework, as it allegedly is
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