Improving Eco-Efficiency Through Waste Reduction Beyond

Article Improving Eco-Efﬁciency through Waste Reduction beyond the Boundaries of a Firm: Evidence from a Multiplant Case in the Ceramic Industry

Guido J. L. Micheli * ID , Enrico Cagno and Elena Tappia Department of Management, Economics and Industrial Engineering, Politecnico di Milano, 20156 Milano, Italy; [email protected] (E.C.); [email protected] (E.T.) * Correspondence: [email protected]; Tel.: +39-02-2399-4056

Received: 1 December 2017; Accepted: 8 January 2018; Published: 11 January 2018

Abstract: To pursue eco-efficiency, one of the most important principles is the sustainable use of resources. The challenge in resource use improvement lies in a clear assessment of resource utilization. However, this evaluation is currently performed within the scope of a company and such an approach is not sustainable anymore in a world with increasingly complex production systems. This paper provides a decision support system (DSS) to disclose where wastes absorb resource capacity of a whole production system beyond the boundaries of a firm. In this way, an intervention priority plan can be established to effectively improve the eco-efficiency of production systems by considering interactions among players of a multiplant or supply chain context. An implementation of the DSS is proposed for the ceramic industry to test it and explore the potential benefits. Results confirm that the DSS can effectively enable different actors to understand how significant inter-firm saving opportunities can be identified.

Keywords: eco-efﬁciency; waste reduction; production system; DSS; ceramic industry; multiplant case

1. Introduction The search for sustainability is currently a highly relevant research topic, as well as a priority for industries across the globe. Eco-efficiency is well recognized as a key management philosophy to generate sustainable improvements by encouraging companies to pursue for environmental improvements that yield simultaneously economic benefits. One of the most important principles is represented by the sustainable use of resources. In fact, trends such as growth of world population, global energy demand, and economic activity have led to a substantial increase in the global demand for resources since the start of the 20th century. As resource supplies are limited and cannot meet the requirements of steady growth, the problem of scarcity will tend to grow to more acute extent in the future. Europe has begun to become aware of the urgent need for a change of direction, and the “Roadmap to a Resource Efficient Europe” has been initiated towards a greener economy heading for lower environmental impacts, while keeping a high standard of living as well as economic competitiveness [1]. In order to meet the needs of the present without compromising the abilities of future generations, the manufacturing industry, as one of the main resource consumers (European Parliament 2012), plays a key role [2,3]. In such a context, increasing resource efficiency, that is, improving productivity and reducing production costs while simultaneously negative impacts on the environment [4,5], appears to be coming of age [6]. As material and energy costs represent at least 50% of the overall costs of manufacturing companies, European industries have anticipated potential savings of around $630 billion US per year through improved use of resources [7].

Sustainability 2018, 10, 167; doi:10.3390/su10010167 www.mdpi.com/journal/sustainability Sustainability 2018, 10, 167 2 of 16

Even though resource efficiencies can be achieved through purchasing [8], it is in reducing waste at all stages in the production of a product that the large savings can be made [9,10]. Resource losses in production mean a non-productive and huge amount of input in the upstream chain and a considerable increase in the total cost. This comes about because businesses pay multiple times for their resources. Not only do they pay to purchase resources and pay to dispose materials that end up as waste, they also pay for labour, energy, and material costs associated with generating, storing, and handling the wastes. Despite the strong need for waste reduction in industry, enhancing operational resources usage is a complex task when considering production systems, namely, multiplant systems, networks, districts or supply chains. In such an environment, flows merge together and single system parts influence each other. Companies may often experience synergies or contrasting impacts from the same intervention [11,12]. Moreover, also the increasing complexity of supply network is making resource efficiency more and more challenging [13,14]. However, collaboration and visibility among players is a well-known approach to shift the focus from the individual company to the entire production system and improve overall sustainability both in production systems [15], as well as in other contexts such as the logistics service industry [16]. When it comes to improving existing production systems by reducing waste, the evaluation of production systems is an activity of high relevance [4,17]: evaluations enable companies to determine values or results of an operating system or a change of system, and therefore represent the base for relevant decisions in production environments. Several papers have proposed methods to evaluate industrial resource efficiency (e.g., [18,19]). However, not all the approaches take an eco-efficiency perspective and there is a lack of decision support systems based on a system-wide evaluation procedure for operational resources improvement in production systems [20]. Currently, the evaluation and assessment of materials and energy utilization are performed within the scope of a company in the most cases [2,21]: companies often do not have direct control over the activities performed and resources consumed by their partners. In most cases, they are involved in activities that generate a large amount of waste, without knowing how much it costs to perform those activities, even though they directly affect the competitive posture of the firm and the entire production system. In increasingly complex supply networks, boosting resource efficiency via synergies between companies is the most complicated route to resource efficiency, but it can allow companies to tap the large saving that is “locked” in the interfaces between companies. More importantly, the action on the interface processes is often more effective (in terms of impact on key performance) than that on internal processes [10,22]. Competitiveness of companies, therefore, can be strongly improved by focusing on the interface processes with other supply chain members. This would offer the greatest rewards in both long-term environmental and economic savings [23]. Despite the extensive literature coverage on eco-efficiency in industry, waste reduction in production systems seems to be understudied. The objective of the paper is to propose a decision support system (DSS) for assessing the overall eco-efficiency performance and supporting waste reduction of a process system, intended as a multiplant system, a network, a districts or a supply chain, considering interactions among players and with an eco-efficiency perspective. The potential benefit from the adoption of such decision support system is shown with reference to a multiplant case study in the ceramic industry. The next section summarizes the most relevant contributions provided by the literature on existing approaches to evaluate industrial resource efficiency. Section3 described the DSS, whereas Section4 illustrates the case study. The result discussion can be found in Section5 and conclusions are reported in Section6.

2. Research Background During the last decades, academic literature has put effort on building in-depth analysis for resource performance assessment. In order to understand the main gaps in existing approaches, a Sustainability 2018, 10, 167 3 of 16 broad search was conducted. We searched databases of scientific journals for relevant methodological peer-reviewed articles on both Google Scholar and Scopus online search engines, with no exclusion/inclusion criterion related to timespan. We used different keyword combinations based on the following set: resource; waste; decision making; assessment; method; supply chain; environment; energy efficiency; resource efficiency. We also performed regular web searches, looking for examples of resource assessment methods used in the industry or developed at universities, but not necessarily published in the scientific journals we have surveyed. Finally, we cross referenced our findings with the lists of methods and tools used by SPIRE (sustainable process industry through resources and energy efficiency)-funded projects STYLE [24] and MEASURE [25] in their survey. The search yielded over one hundred potential contributions including different methodologies. In line with objective of the paper, that is, to provide a DSS for waste reduction, we selected among them those with the highest potential to give inside information on operational resource usage to the high-level decision makers in production systems. Through such a logic, 17 methods were retained. For instance, quantitative methods such as data envelopment analysis that has been widely proposed to perform efficiency analysis in a variety of contexts (e.g., [26,27]), were excluded as their scope is to provide summarising indicators. Note that traditional cost accounting methods are not included in the analysis, as they have a strong departmental orientation and most of the material costs are direct costs (and therefore, assigned directly to products). Table1 summarises the comparison of the selected approaches according to the following six dimensions:

• Material efficiency, that is, whether the assessment of water, raw, indirect and other materials is included; • Energy efficiency, that is, whether the assessment of direct and indirect energy efficiency is included; • Eco-efficiency perspective, that is, whether the resource usage and the related economic implications are assessed jointly; • Cost allocation, that is, whether the cost allocation is considered and if it is accurately performed; • System perspective, that is, whether the assessment is performed at a plant, company, multiplant or supply chain level; • Results as absolute values, that is, whether the application provides absolute values useful for internal analysis, instead of relative values, useful only for comparative analysis.

In the table, each approach is scored with reference to each dimension on the following scale: fully satisfied, partially satisfied or not satisfied. Interesting considerations can be drawn from Table1:

• Eight approaches out of 17 do not take an eco-efficiency perspective. They can be called “Resource use-driven methods”, whereas the others approaches are “Resource cost-driven methods” as they intended to assess resource usage (in terms of physical units) and its economic implications. • Among contributions that take an eco-efficiency perspective, almost all the approaches provide a limited accuracy of cost allocation. • Most approaches do not consider a holistic perspective. In the most of cases, the resource usage and therefore the identification of the sources of inefficiencies of a production system is at single plant or company level. Sustainability 2018, 10, 167 4 of 16

Table 1. Approaches to evaluate industrial resource efficiency (legend: F = Fully satisfied; P = Partially satisfied; “/” = Not satisfied). Energy System Material Efficiency Efficiency Approach Results as Perspective Perspective Eco-Efficiency Cost Allocation Absolute Values

Life Cycle Assessment (LCA) [28]FF//PF Material Input Per Service (MIPS) [29]P///PF Cumulative Energy Demand (CED) [30]/F//PF Exergetic Life Cycle Assessment (ELCA) [31]FF//FF Material Flow Analysis (MFA) [32]F///FF Material and Energy Flow Analysis (MEFA) [18]FF//FF Exergy Analysis [33]FF//FF Hot-Spot Analysis [34]FF//F/ Life Cycle Activity Analysis (LCAA) [35]PPFFPF Life Cycle Costing (LCC) [36]PPFPPF Environmental Life Cycle Costing (E-LCC) [37]FFFPPP Environmental Full Cost Accounting (EFCA) [38]PPFPPF BASF’s Eco-Efﬁciency Analysis [39]FPP/F/ ESSENZ [40]PPP/PF Material Flow Cost Accounting (MFCA) [19]FFFPFF Activity-Based Costing & Environmental FFFPFF Management (ABC&EM) [41] Extended Activity-Based Environmental Costing FFFFPF (ExtABEC at company level) [6]

Among contributions that take an eco-efficiency perspective, the last three approaches reported in the table are the most completed. Material Flow Cost Accounting (MFCA) aims at improving resource and cost efficiency by proposing a material flow oriented analysis that improves the visibility on the material flows in both physical and monetary terms. Thanks to the focus on materials, such approach can be applied at different levels, from individual process steps to supply chain. However, MFCA is restricted to an arbitrary cost allocation rule, namely, the mass ratio that is not appropriate neither from an environmental and life cycle perspective nor from accounting purposes. ABC&EM integrates Activity Based Costing (ABC) and Environmental Management (EM), thus providing a suitable approach for the allocation of environmental costs. The main contribution of this integration is to help managers in understanding how to allocate environmental cost to each product more accurately through cost drivers. However, this integration does not take into account wastes as output of a process by allocating costs only to good finished products. Compared to MFCA and ABC&EM, Extended Activity-Based Environmental Costing (ExtABEC) is more effective in cost allocation even if it is applied at company level. The logic behind ExtABEC is based on Activity Based Costing but, unlike traditional ABC, it considers as cost objectives of a production system also the by-products and waste. The concept of ‘non-product output’ or ‘waste and by-product’ enables a better understanding of the use of available resources. In addition to the actual costs of disposal, the ‘non-product output’ costs also include the resources value lost in waste and by-products generation, considering also the stage at which waste is produced [6,8,42]. As shown in Figure1, ExtABEC considers resources, activities (split in ‘support’ and ‘core’ activities) and cost objectives (i.e., products, by-products and waste). In this way, this approach considers both those costs of resources that are accounted by means of activities and those that are directly accounted to the objects, thus overcoming the traditional control system for waste management that is mainly based on physical unit information and not on monetary values. Sustainability 2018, 10, 167 5 of 15

the objects, thus overcoming the traditional control system for waste management that is mainly Sustainabilitybased on physical2018, 10, 167 unit information and not on monetary values. 5 of 16

FigureFigure 1.1. ResourceResource ﬂowsflows toto costcost objectsobjects inin ExtABECExtABEC (at(at companycompany level)level) [[6].6].

In order to contribute to previous literature by addressing the emerged research gap, this paper In order to contribute to previous literature by addressing the emerged research gap, this paper extends the ExtABEC at a company level as this is the only existing approach that takes an eco- extends the ExtABEC at a company level as this is the only existing approach that takes an eco-efficient efficient perspective and, at the same time, enable to find out where and how major industrial waste perspective and, at the same time, enable to find out where and how major industrial waste absorb absorb resource capacity. The proposed extension is towards to a DSS for waste reduction in resource capacity. The proposed extension is towards to a DSS for waste reduction in multiplant multiplant contexts, where significant improvement in eco-efficiency of a production system can be contexts, where significant improvement in eco-efficiency of a production system can be reached. reached. And ExtABEC (at the company level) can be effectively innovated to across factory And ExtABEC (at the company level) can be effectively innovated to across factory boundaries, as it is boundaries, as it is based on the ABC approach that is widely recognised as suitable, for instance, for based on the ABC approach that is widely recognised as suitable, for instance, for application across application across company functions (e.g., [13,14]). company functions (e.g., [13,14]).

3.3. AA DSSDSS forfor WasteWaste ReductionReduction inin MultiplantMultiplant ProductionProduction SystemsSystems

3.1.3.1. GoalGoal andand ScopeScope TheThe proposedproposed DSSDSS aimsaims toto assessassess thethe overall eco-efficiencyeco-efficiency performance of a production system, whilewhile evaluatingevaluating thethe efficiencyefficiency ofof resourceresource utilization,utilization, asas wellwell asas thethe costscosts relatedrelated toto inefficiencies,inefficiencies, notnot onlyonly atat singlesingle plantplant oror companycompany levellevel butbut alsoalso atat aa productionproduction systemsystem levellevel (Figure(Figure2 2).). Specifically,Specifically, differentlydifferently fromfrom ExtABEC,ExtABEC, itit cancan bebe effectivelyeffectively usedused inin multiplantmultiplant andand supplysupply chainchain contextscontexts toto understandunderstand wherewhere thethe largestlargest resourceresource losseslosses occuroccur oror wherewhere majormajor industrial wasteswastes absorb resources capacitycapacity allall alongalong aa productionproduction routeroute byby assessingassessing thethe impactsimpacts ofof interventionsinterventions notnot onlyonly atat singlesingle companycompany level,level, butbut alsoalso atat thethe system-widesystem-wide level.level. TheThe frameworkframework fosterfoster informedinformed andand sustainablesustainable decision-makingdecision-making processesprocesses byby mappingmapping interconnectedinterconnected resourceresource flowsflows dealingdealing withwith differentdifferent actorsactors inin the same same production production system. system. This This would would ensure ensure a real a progress real progress in the use in theof resources use of resources by avoiding by avoidingimplementing implementing interventions interventions with contrasting with contrasting impacts impactson the onplayer the playerinvolved. involved. In this In way, this way, top topmanagement management can canhold hold useful useful inside inside information information about about resource resource intensive intensive operations, operations, and how and much how muchis spent is spenton materials on materials and energy and energy inputs inputs and andwaste. waste. Such Such information information are areprecious precious in order in order to to(i) (i)identify identify where where the the greatest greatest opportunities opportunities for for effi efficienciesciencies and and costs costs savings savings lie at thethe system-widesystem-wide level;level; (ii)(ii) establishestablish aa correctcorrect interventionintervention prioritypriority planplan toto improveimprove thosethose areasareas thatthat demonstratedemonstrate thethe greatestgreatest improvementsimprovements toto eco-efficiencyeco-efficiency performance;performance; (iii) (iii)enhance enhancethe the sharingsharing ofof knowledgeknowledge andand bestbest practicespractices transfertransfer betweenbetween actorsactors involvedinvolved inin thethe samesame process.process. Sustainability 2018, 10, 167 6 of 16 Sustainability 2018,, 10,, 167167 6 of 15

Figure 2. Goal and scope of decision support system (DSS). FigureFigure 2. 2.Goal Goaland andscope scope of of decision decision support support system system (DSS). (DSS).

The presented DSS can be implemented on Microsoft Office-based applications or embedded in The presented DSS can be implemented on Microsoft Ofﬁce-based applications or embedded systems that are more sophisticated. It can be applied to any production system for which all the in systems that are more sophisticated. It can be applied to any production system for which all the inputs and outputs of each production unit can be quantified. The DSS applicability is especially for, inputs and outputs of each production unit can be quantiﬁed. The DSS applicability is especially for, but not limited to, process industries because they have a high dependence on resources (energy, raw but not limited to, process industries because they have a high dependence on resources (energy, raw materials, and water) in their production and they share the potentially high impact they may have materials, and water) in their production and they share the potentially high impact they may have on on the environment through their daily operations. the environment through their daily operations. 3.2. DSS’s Description 3.2.3.2. DSS’sDSS’s Description Description There are three fundamental components of the DSS proposed, as Figure 3 shows. ThereThere are are three three fundamental fundamental components components of of the the DSS DSS proposed, proposed, as as Figure Figure3 shows.3 shows.

FigureFigure 3. 3.Components Componentsof ofDSS. DSS.

The first component is a database management system (DBMS), which serves as a data bank. It TheThe ﬁrstfirst componentcomponent isis a database management sy systemstem (DBMS), (DBMS), which which serves serves as as a adata data bank. bank. It stores data that are relevant to the class of problems for which the DSS is used. As the DSS proposed Itstores stores data data that that are are relevant relevant to to the the class class of of prob problemslems for which thethe DSSDSS isis used.used. AsAs thethe DSSDSS proposedproposed is presented as a customizable tool (due to the complexity of the decision-making process involved), isis presented presented as as a a customizable customizable tool tool (due (due to to the the complexity complexity ofof thethe decision-makingdecision-making processprocess involved),involved), the available information depends strongly on the specific context (e.g., in terms of the industrial thethe availableavailable informationinformation dependsdepends stronglystrongly onon thethe speciﬁcspecific contextcontext (e.g.,(e.g., inin termsterms ofof thethe industrialindustrial sector and type of production systems), according to kind of business relationship, length of the sectorsector and and type type of of production production systems), systems), according according to kind to kind of business of business relationship, relationship, length length of the chain,of the chain, decisional symmetry degree, and quality of available information. decisionalchain, decisional symmetry symmetry degree, degree, and quality and quality of available of available information. information. A model-base management system (MBMS) represents the second component. It transforms AA model-base model-base management management system system (MBMS) (MBMS) represents represents the secondthe second component. component. It transforms It transforms data data from the DBMS into information that is useful in decision making, by using a new version of the fromdata thefrom DBMS the DBMS into informationinto information that that is useful is useful in decision in decision making, making, by by using using a newa new version version of of the the Extended Activity-Based Environmental Costing model. This component is neither inflexible nor rigid: as the model is complex, this part is built in such a way that makes the model transparent to Sustainability 2018, 10, 167 7 of 16

ExtendedSustainability Activity-Based 2018, 10, 167 Environmental Costing model. This component is neither inflexible nor7 rigid: of 15 as the model is complex, this part is built in such a way that makes the model transparent to users. Inusers. this In way, this decision way, decision makers makers are aware are ofaware how theof how system the variablessystem variables are interrelated, are interrelated, and they and can they also modifycan also variables modify variables of the model, of the according model, according to the specific to the problem specific and problem context and of application.context of application. The model takesThe model its origin takes from its theorigin Extended from the Activity-Based Extended Activity-Based Environmental Environmental Costing (at company Costing level); (at company however, unlikelevel); however, this method, unlike it considers this method, not onlyit considers resource, not activity only resource, and cost activity objects and flows cost of objects the single flows unit of (plantthe single or company) unit (plant [6 ],or but company) also flow [6], synergies but also of flow the wholesynergies production of the whole system production to which thesystem single to unitswhich belong the single (Figure units4). belong (Figure 4).

Figure 4. Resource flows to cost objects in ExtABEC (at the company level and system-wide level). Figure 4. Resource flows to cost objects in ExtABEC (at the company level and system-wide level). The third component, a dialog generation and management system (DGMS) is the vehicle for investigatingThe third the component, results. aIt dialog provides generation a set andof graphs management and indexes system (DGMS)reporting is theeco-efficiency vehicle for investigatingperformances the at results.single units It provides and at a seta system-wi of graphs andde level. indexes Considering reporting eco-efficiencythat the DSS performances is based on attechnical single units input-output and at a system-widedata and coefficients level. Considering (i.e., the cost that drivers), the DSS isit basedhas the on advantage technical input-outputof including datacausal and information coefficients and (i.e., aiding the cost predict drivers),ions of it the has effects the advantage of interventions: of including the DSS causal requires information alternative and aidingschemes predictions as input and of the delivers effects information of interventions: on the the possible DSS requires system alternativebehaviour. schemesIn this way, as input it allows and deliversusers to informationcreate and compare on the possiblealternative system scenarios behaviour. to simulate/assess In this way, impacts it allows of users interventions to create andin a comparewhat/if approach alternative not scenarios only at tolocal simulate/assess level (plant or impacts company) of interventions but also at system-wide in a what/if level approach of a notmultiplant only at or local supply level chain (plant context. or company) but also at system-wide level of a multiplant or supply chainHence, context. the proposed DSS enrich previous contribution as: Hence, the proposed DSS enrich previous contribution as: • It considers both material and energy efficiency; • It considerstakes into both account material not andonly energy the operational efficiency; and environmental perspective, but also the • Iteconomic takes into one; account not only the operational and environmental perspective, but also the • economicThe cost allocation one; is based on Activity-Based Costing and therefore it is accurately performed; • TheIt assesses cost allocation both the islocal based and on global Activity-Based impact of alternative Costing and interventions therefore it to is improve accurately eco-efficiency, performed; • Itin assessesorder to bothimplement the local the and more global suitable impact interv of alternativeentions for interventions a whole eco-efficient to improve improvement eco-efficiency, of ina production order to implement system, without the more worsening suitable interventions the performance for a of whole the single eco-efficient units; improvement of a • productionIt provides system,the absolute without physical worsening and monetary the performance values of of the the products, single units; wastes and by-products • Itof providesa production the absolute system. physical and monetary values of the products, wastes and by-products of a production system. Sustainability 2018, 10, 167 8 of 16 Sustainability 2018, 10, 167 8 of 15

3.3.3.3. Steps Steps TheThe DSS DSS proposed proposed can can be be effectively effectively used used to to su supportpport decision decision making making with with respect respect to to the the enhancementenhancement of of the the overall overall production production system system pe performancerformance in in both both environmental environmental and and economic economic terms.terms. In In terms terms of of outcome, outcome, in in fact, fact, it it delivers delivers a a li listst of of likely likely eco-efficiency eco-efﬁciency enhancement enhancement interventions interventions toto be be implemented implemented that that fit ﬁt within within the the budget, budget, time time,, and and cost cost constraints constraints of of companies. companies. The The proposed proposed approachapproach can can then then be be considered considered a a solid solid basis basis to to a a continuous continuous improvement process (Figure 5 5).).

FigureFigure 5. 5. TheThe four four steps steps of of DSS. DSS.

TheThe DSSDSS employs employs four four steps: steps: (i) boundaries (i) boundaries and process and modelling, process (ii)modelling, ExtABEC implementation,(ii) ExtABEC implementation,(iii) resource efﬁciency (iii) resource analysis, efficiency and (iv) an interventionsalysis, and (iv) evaluation. interventions evaluation.

1.1. BoundariesBoundaries and and process process modelling modelling. The. The boundaries boundaries of the of theproduction production system system to be to analysed be analysed are identified.are identified. Then, Then, among among all the all thepossible possible set setof ofprocesses processes of ofthe the production production system system under under examination,examination, users users identify identify the the most most critical critical to to be be assessed assessed and and improved. improved. The The analysis analysis then then identifiesidentifies the the major major functions functions performed performed by by each each member member involved involved in in the the process. process. 2.2. ExtABECExtABEC implementation. implementation. ThisThis step step implies implies the the following following activities: activities: 2.1 Identification of the cost objects: products, by-products and wastes are selected. 2.1 Identification of the cost objects: products, by-products and wastes are selected. 2.2 Identification and quantification of the resources: all the resources used all along the 2.2 Identification and quantification of the resources: all the resources used all along the process under analysis are identified and quantified. Resources include, for example, process under analysis are identified and quantified. Resources include, for example, energy, raw materials, water, labour, and indirect materials. energy, raw materials, water, labour, and indirect materials. 2.3 Identification of the core activities: the way that activities consume resources is identified. 2.3 Identification of the core activities: the way that activities consume resources is identified. The process must be broken down into the specific activities performed by each component The process must be broken down into the specific activities performed by each component of the production system. The analysis involves determining what activities are done within of the production system. The analysis involves determining what activities are done the production system, how many people, resources and time are required to perform each within the production system, how many people, resources and time are required activity, and what operational data best reflect the performance of the activities. to perform each activity, and what operational data best reflect the performance of 2.4 Identification of the support activities: the activities that do not have a direct influence on the activities. products but are necessary for the process, because they support other primary activities, 2.4 are Identificationidentified. of the support activities: the activities that do not have a direct influence on 2.5 Identificationproducts but and are quantification necessary for of the the process, drivers because describing they the support correlation other between primary activities activities, andare support identified. activities. 2.62.5 IdentificationIdentification of andthe quantificationresource drivers of theand drivers quantification describing of the their correlation intensities: between the way activities that activitiesand support adsorb activities. resources is identified. 2.72.6 AssignmentIdentification of the of theresources resource to driverscost objects: and quantification when possible, of theirresources intensities: can be the accounted way that directlyactivities to the adsorb cost objects. resources is identified. Sustainability 2018, 10, 167 9 of 16

2.7 Assignment of the resources to cost objects: when possible, resources can be accounted directly to the cost objects. 2.8 Assignment of the resources to activities: otherwise, resources can be accounted, by means of the resource drivers, to the activities they are used by. The activity cost represents the total cost of resources used to perform a specific unit of work. 2.9 Identification of the activity drivers and quantification of their intensities: the way that cost objects absorb resources by means of activities is identified. 2.10 Assignment of the activities: by means of the activity drivers, the value of the activities is accounted to the cost objects. 2.11 Calculation of the cost of the products/wastes/by-products: for every cost object, the share of resources directly accounted and the share indirectly accounted through the activities is summed up. 3. Resource efficiency analysis. Thanks to flow and cost allocation carried out through ExtABEC implementation, it is possible to identify inefficiencies all along the production route (inefficiencies that are related to resources and activities value lost in the production of wastes instead of saleable products). In this way, players involved in the production route can effectively analyse resource consumption and waste generation of the system, by assessing not only single company performance but also the overall eco-efficiency of the production system analysed. 4. Interventions evaluation. To support decision-making, the potential impacts of the individual actions on the examined process are evaluated at different levels (single unit and system-wide), in order to choose improvement interventions that do not worsen the overall eco-efficiency of the production system examined. Considering that the DSS is based on technical input-output format and on coefficients (the cost drivers of ExtABEC), it effectively allows to develop and compare alternative scenarios. With this regard, the adoption of different technologies, the use of different materials, the selection of different suppliers can be evaluated to adopt the best local decision leading to a whole improvement of the eco-efficiency of the production system. The resulting changes in resource and activity costs can be traced to specific product to determine the effect on different players and therefore quantify the eco-efficiency improvement at both local and global level. Therefore, DSS effectively allows the user to develop and compare alternative scenarios to adopt the best local decision leading to a whole improvement of the eco-efficiency of the production system analysed.

4. Description of the Multiplant Case Study The DSS was implemented in Microsoft Excel in an input-output format (Figure6), with the twofold objective of testing and applying it using a real case. The case study is represented by an Italian ceramic company (Modena, Italy), which consists of two plants producing floor and wall tiles [43]. These two companies are autonomous and local managed, thus allowing referring to them as two distinct companies, named ‘Company 1’ and ‘Company 2’ in the rest of the paper. However, Company 1 is the focal company in relationship with Company 2. Ceramic manufacturing is characterized by (almost) the nonexistence of material losses [44–46]. Indeed, any company recycles and re-uses almost all parts of the accumulated process loss within the plant due to product specifications or process requirements. Materials that cannot be recycled internally leave the plant and are supplied to other plants. Due to this, the costs associated with product losses traditionally refer only to disposal costs. The ExtABEC method, instead, highlights resource costs that are irrecoverably lost in the production. It is not possible, for various reasons, to completely prevent the production of waste or by-products; however, it is useful to try to reduce waste as much as possible while preserving the high level and quality of good output. The general process of manufacturing glazed single-fired ceramic tiles, the object under analysis, is rather uniform and it consists of two different stages. The first stage relates to the body manufacturing Sustainability 2018, 10, 167 10 of 16 which includes raw materials acquisition, mix preparation, forming, and drying, and the glaze preparation, which includes glaze raw materials acquisition, frit preparation, and grinding. The second stage involves laying the glaze on the body, which is called decoration, and the subsequent firing of

Sustainabilitythe glaze body. 2018, 10, 167 10 of 15

Figure 6. DSS interface for Company 1. Figure 6. DSS interface for Company 1. Regarding the waste, a European project led by the research center Instituto de Tecnología CerámicaRegarding (ITC) has the shown waste, that a European the following project wast lede products by the research are generating center during Instituto the de process: Tecnolog ía Cerámica (ITC) has shown that the following waste products are generating during the process: • Crude waste. This is formed by unfired materials. •• CookedCrude waste. waste. This This is is formed the fired by materials unfired materials. generated in the firing. •• Sludge.Cooked This waste. consists This is of the the fired sludge materials obtained generated in the cleaning in the firing. of the glaze mills. •• WasteSludge. water. This consistsIt is mainly of the generated sludge obtained from cleaning in the cleaningwater in ofpreparation the glaze mills. and casting units, and • inWaste various water. processing It is mainly activities. generated from cleaning water in preparation and casting units, and in • Exhaustedvarious processing lime. It is activities. generated in the glaze production stage and during the firing process. • TypicalExhausted by-products lime. It is are generated excessive in thespray-dried glaze production powder produced stage and duringin the spray-drying the firing process. stage and excessiveTypical ceramic by-products glaze produced are excessive in the spray-dried glaze production powder process. produced in the spray-drying stage and excessiveFirstly, ceramic an analysis glaze producedof the current in the scenario glaze production is carried process. out (AS-IS case). Then, impacts of due scenariosFirstly, are an assessed analysis at ofplant the currentand system scenario levels. is carriedScenario out 1 deals (AS-IS with case). a potential Then, impacts improvement of due interventionscenarios are planned assessed by at Company plant and 1, systemwithout levels. having Scenario a system-wide 1 deals perspective with a potential that means improvement without lookingintervention at the planned potential by Company impacts on 1, without Company having 2. Scenario a system-wide 2, instead, perspective considers that meansan alternative without improvementlooking at the intervention potential impacts Company on Company1 could carry 2. Scenarioout if it considers 2, instead, the considers potential an impacts alternative this interventionimprovement could intervention have not Company only on its 1 could own carryplant, outbut ifalso it considers on Company the potential 2 and on impacts the whole this productionintervention system. could have In both not scenarios, only on its input own plant, data of but Company also on Company 1 are assumed 2 and onto thebe equal whole to production the input datasystem. of AS-IS In both case, scenarios, both in inputphysical data and of Companymonetary 1units. are assumed This means to be that equal any to reduction the input in data waste of AS-IS and orcase, by-products both in physical amount and produced monetary by units. Company This means 1 and/or that any reductionreduction inin waste resources and orand by-products activities valueamount lost produced in ‘non-output’ by Company generation 1 and/or are translated any reduction into an in increase resources of the and resources activities and value activities lost in ‘non-output’value allocated generation to saleable are products translated and into an an increase increase of of good the resources output quantities. and activities This value is a allocatedreasonable to assumptionsaleable products coming and from an increase[47], who of showed good output that firms quantities. can attain This the is a maximum reasonable level assumption of good comingoutput allowedfrom [47 by], whotheir showedendowment that of firms inputs, can while attain simultaneously the maximum levelreducing of good waste. output allowed by their endowment of inputs, while simultaneously reducing waste. 5. Results and Discussion In the case study, Company 1, in AS-IS scenario, founds that crude waste represents the one waste with the higher full industrial cost (as Table 2 and Figure 7 show).

Sustainability 2018, 10, 167 11 of 16

5. Results and Discussion In the case study, Company 1, in AS-IS scenario, founds that crude waste represents the one waste with the higher full industrial cost (as Table2 and Figure7 show). Sustainability 2018, 10, 167 11 of 15 Sustainability 2018, 10, 167 11 of 15 Table 2. Full industrial cost of wastes and by-products of Company 1 in AS-IS case. TableTable 2. 2. Full Full industrial industrial costcost ofof wastes andand by-productsby-products of of Company Company 1 in1 inAS-IS AS-IS case. case. Waste and by-Product From Resources (€) From Activities (€) Full Industrial Cost (€) WasteWaste and and by-Product by-Product FromFrom ResourcesResources (€)(€) FromFrom Activities Activities (€) (€) FullFull Industrial Industrial Cost Cost (€) (€) CrudeCrude wasteCrude waste waste 5452 5452 27,318 27,318 27,318 32,770 32,770 32,770 CookedCookedCooked waste waste waste 5352 5352 17,812 17,812 17,812 23,164 23,164 23,164 Spray-driedSpray-driedSpray-dried powder powder powder 10,904 10,904 10,904 9827 9827 9827 20,731 20,731 20,731 SludgeSludgeSludge 109010901090 15,49115,491 15,491 16,58116,581 16,581 WasteWaste waterWaste water water 218 218 15,591 15,591 15,591 15,809 15,809 15,809 GlazeGlazeGlaze 98609860 32093209 3209 13,06913,069 13,069 Exhausted lime 1090 5699 6789 ExhaustedExhausted lime lime 1090 5699 5699 6789 6789 Packaging waste 2784 1128 3912 PackagingPackaging waste waste 2784 1128 1128 3912 3912 TOTAL 36,750 96,075 132,825 TOTALTOTAL 36,75036,750 96,07596,075 132,825132,825

Figure 7.FigureRelative 7. Relative importance importance of wastes of wastes and and by-products by-products of of Company Company 1 on 1 onthe theoverall overall full industrial full industrial cost in AS-IS case. cost inFigure AS-IS 7. case. Relative importance of wastes and by-products of Company 1 on the overall full industrial cost in AS-IS case. For this reason, in Scenario 1, in which the DSS is used at single plant level without considering Forinformation thisFor reason, this reason, about in Scenario Company in Scenario1, 2, init1, is whichin reasonable which the the DSSto DSS invest is is used usedin better at single presses plant plant to decrease level level without the without resource considering considering and informationinformationactivities about value about Company lost Company in waste 2, it generation,2, is itreasonable is reasonable as pressing to to invest in vesthas been inin better identified presses presses as thatto to decrease activity decrease mostthe the resource involved resource and and activitiesactivitiesin value crude value lost waste in lost wastegeneration in waste generation, generation,(in terms as of pressingas value pressing lost). has has In been beenScenario identiﬁed identified 2, in which as as thatthat the activity DSS ismost most used involved involvedat a in multiplant level, instead, Company 1 finds that the spray-dried powder from Company X (i.e., a in crude waste generation (in terms of value lost). In Scenario 2, in which the DSS is used at a crude wastecompany generation outside (inthe termsmultiplant of value contexts) lost). represents In Scenario the main 2, in resource which the causing DSS isthe used generation at a multiplant of multiplant level, instead, Company 1 finds that the spray-dried powder from Company X (i.e., a level, instead,crude waste Company in Company 1 ﬁnds 2, as thatwell as the big spray-driedresource and activity powder value from loss. Company Note that crude X (i.e., waste a has company company outside the multiplant contexts) represents the main resource causing the generation of outside the highest multiplant impact contexts) on full industrial represents cost for the Company main resource 2 (Figure causing 8). the generation of crude waste crude waste in Company 2, as well as big resource and activity value loss. Note that crude waste has in Company 2, as well as big resource and activity value loss. Note that crude waste has the highest the highest impact on full industrial cost for Company 2 (Figure 8). impact on full industrial cost for Company 2 (Figure8).

Figure 8. Relative importance of wastes and by-products of Company 2 on the overall full industrial cost in AS-IS case.

FigureFigure 8. Relative 8. Relative importance importance of wastesof wastes and and by-products by-products ofof Company 2 2on on the the ov overallerall full full industrial industrial cost in AS-IS case. cost in AS-IS case. SustainabilitySustainability2018 2018, 10, 10, 167, 167 1212 of of 16 15

For this reason, Company 1 takes into account the possibility of investing in facilities to convert crudeFor waste this reason, into spray-dried Company 1 takespowder into to account satisfy the Company possibility 2’s of need investing for higher in facilities quality to convertpowder. crudeScenario waste 2 was into recognized spray-dried as powder the one to leading satisfy Companyto the biggest 2’s needeco-efficiency for higher improvement quality powder. of both Scenario single 2 wasplant recognized and whole as production the one leading system to context the biggest (Figure eco-efﬁciency 9). improvement of both single plant and whole production system context (Figure9).

FigureFigure 9. 9.Comparison Comparison AS-IS AS-IS case case vs vs Scenario Scenario 2 of2 of main main material material ﬂows flows in in a multiplanta multiplant perspective. perspective.

ResultsResults confirm confirm that that the the DSS DSS proposed proposed allows allows assessing assessing the the resource resource usage usage and and therefore therefore identifyingidentifying the the sources sources of of inefficiencies inefficiencies of of a a production production system system at at a a multiplant multiplant level, level, in in order order to to evaluateevaluate improvement improvement interventions interventions without without contrasting contrasting impacts impacts for for the the actors actors involved. involved. Moreover,Moreover, the the DSS DSS proposed proposed allows allows eco-efficiency eco-efficiency evaluations evaluations independently independently of of the the user: user: low, low, middle,middle, or or top top management management for for single single plant plant (Scenario (Scenario 1), 1), or or for for a a system-wide system-wide context context (Scenario (Scenario 2). 2). Indeed,Indeed, it it is is implemented implemented in in Microsoft Microsoft Excel Excel in in an an input-output input-output format format that that is is quite quite easy easy to to use use (almost(almost everybody everybody can can useuse it),it), and it it is is available available quite quite readily. readily. The The DSS DSS works works independently independently from fromthe theindustry, industry, as the as thesystem system is developed is developed in a in modular a modular way way in inorder order to tobe beindependent independent of ofthe thecharacteristics characteristics of ofthe the low low control control levels levels that that will will feed feed it with it with process process data, data, according according to the to the level level and andquality quality of ofavailable available information information (real, (real, estimated, estimated, or or supposed). supposed). In In the case study,study, the the data data are are quite quite accurate,accurate, as as the the two two companies companies belong belong to to the the same same multiplant multiplant context, context, which which is is characterized characterized by by a a collaborativecollaborative environment. environment. Moreover, Moreover, considering considering that th theat DSSthe DSS is based is based on technical on technical input-output input-output data anddata coefficients and coefficients (i.e., the (i.e., cost drivers),the cost itdrivers), allows usersit allows to develop users andto develop compare and alternative compare scenarios. alternative scenarios.Lastly, it has been shown how the DSS aims at assisting decision-making in a manner that will supportLastly, the identification it has been shown of the sourceshow the of DSS inefficiencies aims at assisting in terms decision-making of resources and in activities a manner value that lost will insupport waste generation. the identification This reduction of the sour inces losses of inefficiencies not only means in terms a considerable of resources decrease and activities in the total value cost lost breakdown,in waste generation. but also ensures This reduction a decrease in oflosses the environmentalnot only means footprint a considerable and therefore decrease contributes in the total to cost a morebreakdown, sustainable but industry. also ensures Moreover, a decrease the DSS of the allows environmental users to map footprint resources and (material, therefore water, contributes energy, to labour)a more and sustainable also by-products industry. and Moreover, waste flows the and DSS to quantifyallows users the utilization to map resources of resources (material, both in termswater, ofenergy, physical labour) and monetary and also units. by-produ In thects case and study, waste only flows the and material to quanti wastefy flowthe utilization (in termsof of quantity) resources wasboth mapped in terms at of single physical plant and and monetary the production units. In system the case level study, in allonly alternatives, the material as waste crude flow waste (in wasterms of quantity) was mapped at single plant and the production system level in all alternatives, as crude Sustainability 2018, 10, 167 13 of 16 identified as the main waste of the two companies. The monetary aspect was instead taken into account by calculating the full industrial cost of wastes and by-products and the inefficiency of the use of the resources in the production process for both Companies 1 and 2 in AS-IS case, Scenarios 1 and 2, in order to assess the resources and activities value lost in ‘non-products’ generation.

6. Conclusions

6.1. Theoretical Application of the DSS in Supply Chain Contexts No reliable references were found with satisfactory data relative to environmental aspects of production, that is, the amount of waste generated at each stage of the production route, and therefore it was not possible to carry out a supply chain analysis. Currently, promoting an integrated overall resource and energy management system to facilitate information flow among the participating companies of a supply chain/network is becoming increasingly similar to the mechanisms typical of multiplant contexts, where companies have collaborative long-term relationships and are more focused on large opportunities in order to gain and maintain competitive advantage [48]. Applying the proposed DSS in a supply chain context requires a common set of cost accounting standards for the total supply chain being calculated based on a shared definition of activities and their cost drivers among all the players leading to the aggregation of supply chain activity-based costs [49]. The key enabler is the visibility on the whole process and all flows. In the case, at least one company in the production system can have such visibility, then the DSS can be applied involving other companies. The DSS can effectively solve problems related to crossing the boundaries of organizations while maintaining the interests of each organization as it allows waste reduction with positive benefits on overall eco-efficiency.

6.2. Scientific Contribution and Industrial Relevance The major scientific contribution consists in extending the application of ExtABEC from a single plant level to a production system level (i.e., multiplant systems, networks, districts or supply chains). To do that, a DSS for process industry optimization based on a system-wide evaluation procedure for operational resource efficiency was developed. The proposed DSS can be implemented on Microsoft Office-based applications or embedded in systems that are more sophisticated, and it can be especially applied but not limited to process industries. It was implemented in Microsoft Excel in order to tested it in a real case. The application to the real case show that the application of ExtABEC at a production system level can enable different actors involved in production systems to understand how their decisions impact the whole production system, and how significant inter-firm saving opportunities can be identified to improve eco-efficiency performances. Even though the DSS focuses on reducing the resources and activities value lost in waste production, it has also positive environmental impacts: materials and energies are better used, natural resource demand is being reduced, as are waste flows burdening the environment. Consequently, the DSS represents a very important tool for environment-oriented management and for improvements of eco-efficiency.

Acknowledgments: The authors acknowledge the relevant contribution of Federica Russo to the research. Author Contributions: All authors were involved in choosing the research methodology, in data analysis, as well as in the result analysis and discussion. All authors wrote a part of the manuscript and have approved the submitted manuscript. Conﬂicts of Interest: The authors declare no conﬂict of interest. Sustainability 2018, 10, 167 14 of 16

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