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Hindawi Publishing Corporation Advances in Decision Sciences Volume 2013, Article ID 326185, 2 pages http://dx.doi.org/10.1155/2013/326185 Editorial Decision Making in Support of Manufacturing Enterprise Transformation Albert Jones, 1 Richard H. Weston, 2,3 Bernard Grabot, 4 and Bernard Hon 5 1 NIST, Gaithersburg, MD 20899, USA 2 MSI Research Institute, Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, Loughborough LE11 3TU, UK 3 Department of Manufacturing and Materials Sciences, Cranfield University, Bedford MK43 0AL, UK 4 University of Toulouse, 31000 Toulouse, France 5 Department of Engineering, Liverpool University, Merseyside L69 3BX, UK Correspondence should be addressed to Albert Jones; [email protected] Received 13 November 2012; Accepted 13 November 2012 Copyright © 2013 Albert Jones et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. To achieve the agility necessary to compete successfully in everchanging world markets, manufacturing enterprises of all sizes must exhibit a transformational leadership. Strategic, tactical, and operational decision making is an essential part of such leadership. e papers in this special issue seek to understand and characterize common transformational decision-making needs in manufacturing enterprises and the state of art in decision-making methods and technologies. Additionally, these papers identify gaps in those methods and technologies and propose research can fill those gaps. In the paper titled “e integrated use of enterprise and system dynamics modelling techniques in support of business decisions” the authors use case studies to describe a new mod- elling methodology for analysing and managing dynamics and complexities in production systems. is methodology is based on a systematic transformation process that integrates enterprise, causal loop (CL), and system dynamics (SDs) modelling techniques. e methodology relies on the cre- ation of CIMOSA process models, which are then converted to CL models. CL models are then structured and translated into equivalent SD models. e authors have used their methodology in a number of case study companies to (1) capture business processes, (2) model the dynamics impact- ing those processes, (3) analyse the impact of variations in customer demand on value realization, and (4) analyse the effect of constant sales orders on material supply, cost, and product realisation. In the paper titled “Performance assessment of product ser- vice system from system architecture perspectives” the author focuses on a concept called Product Service System (PSS). e PSS enables the manufacturers of complex engineering prod- ucts to incorporate support services into the entire product life cycle. However, the PSS design has imposed significant risks to the manufacturer not only in the manufacture of the product itself, but also in the provision of support services over a long period of time at a predetermined price. is paper analysed three case studies using case study research design approach and mapped the service elements of the case studies to the generic Complex Engineering Product Service System (CEPSS) model. By establishing the concept of capability distribution for a PSS enterprise, the capability of the CEPSS can be overlaid on the performance-based reward scheme so that decision makers evaluate options related to the business opportunities presented to them. In the paper titled “Evaluating ethical responsibility in inverse decision support” the author addresses an ethical dilemma in “Inverse Decision Support.” at dilemma arises whenever a decision support analyst (DSA) must evaluate the ethical responsibility in selecting a suboptimal alternative. is can happen, for example, when the actual decision maker requires the DSA’s justification for a preconceived selection that does not correspond to the best option resulted from the professional resolution of the problem. To address this dilemma, the author proposed an extended application
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Hindawi Publishing CorporationAdvances in Decision SciencesVolume 2013, Article ID 326185, 2 pageshttp://dx.doi.org/10.1155/2013/326185
EditorialDecision Making in Support of Manufacturing EnterpriseTransformation
Albert Jones,1 Richard H. Weston,2,3 Bernard Grabot,4 and Bernard Hon5
1 NIST, Gaithersburg, MD 20899, USA2MSI Research Institute, Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University,Loughborough LE11 3TU, UK
3Department of Manufacturing and Materials Sciences, Cranfield University, Bedford MK43 0AL, UK4University of Toulouse, 31000 Toulouse, France5 Department of Engineering, Liverpool University, Merseyside L69 3BX, UK
Correspondence should be addressed to Albert Jones; [email protected]
Received 13 November 2012; Accepted 13 November 2012
Copyright © 2013 Albert Jones et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
To achieve the agility necessary to compete successfully ineverchanging world markets, manufacturing enterprises ofall sizes must exhibit a transformational leadership. Strategic,tactical, and operational decision making is an essential partof such leadership. The papers in this special issue seekto understand and characterize common transformationaldecision-making needs in manufacturing enterprises and thestate of art in decision-making methods and technologies.Additionally, these papers identify gaps in thosemethods andtechnologies and propose research can fill those gaps.
In the paper titled “The integrated use of enterprise andsystem dynamics modelling techniques in support of businessdecisions” the authors use case studies to describe a newmod-elling methodology for analysing and managing dynamicsand complexities in production systems.Thismethodology isbased on a systematic transformation process that integratesenterprise, causal loop (CL), and system dynamics (SDs)modelling techniques. The methodology relies on the cre-ation of CIMOSA process models, which are then convertedto CL models. CL models are then structured and translatedinto equivalent SD models. The authors have used theirmethodology in a number of case study companies to (1)capture business processes, (2) model the dynamics impact-ing those processes, (3) analyse the impact of variations incustomer demand on value realization, and (4) analyse theeffect of constant sales orders on material supply, cost, andproduct realisation.
In the paper titled “Performance assessment of product ser-vice system from system architecture perspectives” the authorfocuses on a concept called Product Service System (PSS).ThePSS enables the manufacturers of complex engineering prod-ucts to incorporate support services into the entire productlife cycle. However, the PSS design has imposed significantrisks to the manufacturer not only in the manufacture of theproduct itself, but also in the provision of support servicesover a long period of time at a predetermined price. Thispaper analysed three case studies using case study researchdesign approach and mapped the service elements of thecase studies to the generic Complex Engineering ProductService System (CEPSS) model. By establishing the conceptof capability distribution for a PSS enterprise, the capability ofthe CEPSS can be overlaid on the performance-based rewardscheme so that decision makers evaluate options related tothe business opportunities presented to them.
In the paper titled “Evaluating ethical responsibility ininverse decision support” the author addresses an ethicaldilemma in “Inverse Decision Support.” That dilemma ariseswhenever a decision support analyst (DSA) must evaluatethe ethical responsibility in selecting a suboptimal alternative.This can happen, for example, when the actual decisionmaker requires the DSA’s justification for a preconceivedselection that does not correspond to the best option resultedfrom the professional resolution of the problem. To addressthis dilemma, the author proposed an extended application
2 Advances in Decision Sciences
of the Analytic Hierarchy Process model. That extendedapplication is consistent with the Inverse Decision Theorythat is used extensively in medical decision making. Theauthor conducted a survey of DSAs to assess their per-spective of using the proposed extended application. Thepaper includes results from the survey. Those results showthat (1) 80% of the respondents felt that the proposedextended application is useful and (2) 14% of them expandedthe usability of the extended application to their academiccourses.
In the paper titled “Design of an integrated methodologyfor analytical design of complex supply chains” the authorsreview modelling capabilities needed to advance industrybest practice regarding the analytical design of supply chains.Those capabilities include (1) the graphical representationand explicit description of key structural properties of com-plex supply chains, (2) behavioural exploration of dynamicproperties of existing complex supply chains, (3) predictionof possible future behaviours of complex supply chains whenuncertainties arise, and (4) predictive quantification aboutrelative performances of alternative complex supply chainconfigurations, including risk assessments, when they aresubjected to uncertainty. They then reviewed alternativemeans of deploying state-of-the-art modelling techniques,including enterprise modelling (EM), causal loop diagram-ming (CLD), and simulation modelling (SM). Previously theliterature had not reported methods of coherently applyingEM, CLD, and SM techniques in support of the lifecycleengineering of complex supply chains. The authors thendescribe their efforts to specify and develop an integrated,model-driven method of modeling and engineering complexsupply chains. This method has the potential to supportcollective and individual decision making of managers andengineers.
In the paper titled “Multiobjective optimization of aircraftmaintenance in thailand using goal programming: a decision-support model” the authors develop a multiobjective opti-mization model in order to evaluate suppliers for aircraftmaintenance tasks, using goal programming. The authorshave developed a two-step process. Authors use the modelas a decision support tool for managing demand, by usingaircraft and flight schedules to evaluate and generate aircraftmaintenance requirements, including spare part lists. In steptwo, they develop a multi-objective optimization model byminimizing cost, minimizing lead time, and maximizing thequality under various constraints in the model. Finally, theydemonstrate the model in the actual airline case study.
In the paper “Modelling framework to support decisionmaking in manufacturing enterprises” the authors describea novel systematic framework for creating coherent sets ofintegrated models that facilitate production planning andcontrol (PPC) strategies in future reconfigurable manufac-turing enterprises (MEs). The framework is the enhancedintegrated modelling framework (EIMF). EIMF supports theengineering of common types of strategic, tactical, and oper-ational processes found in many MEs. The authors use theCIMOSA enterprise modelling approach to develop a struc-tured, model-driven, integrated approach that can supportvarious PPC decisions. This new approach can capture and
represent both static and dynamic aspects of an organization.Finally, the authors provide example application cases thatshow benefits in terms of lead time and cost reductions.
In the paper “Model driven integrated decision-making inmanufacturing enterprises” the authors summarize decision-making requirements and solutions from four world-classmanufacturing enterprises (MEs).They include observationson deployed methods of complexity handling that facilitatemultipurpose, distributed decision making. They also reporton examples of partially deficient “integrated decision mak-ing” which stem from a poor understanding of the relation-ship between structure and behavior. As a way of improvingthis understanding, the authors propose a “reference modelof ME decision- making” and a new model-driven approach,which can “underpin integrated ME decision- making.” Theauthors include an ME case study to explain how theirapproach can improve the integration of previously distinctplanning functions. The modelling approach is particularlyinnovative in respect to the way it structures the coherentcreation and experimental reuse of “fit for purpose” discreteevent (predictive) simulation models at the multiple levels ofabstraction.
Albert JonesRichard H. Weston
Bernard GrabotBernard Hon
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