A multi-criteria decision model for the selection of a computerized manufacturing control system

Ghandforoush, Parviz; Huang, Philip Y.; Taylor, Bron

doi:10.1080/00207548508904695

Cited by 18 publications

(3 citation statements)

References 1 publication

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“…For a review of this work see Shanteau[9]. Most of the work has been done in the socio‐political and economic fields, with little evidence of the thinking being used in operations management[10, 11, 12], added to which one of the major problems of using a weighted evaluation is that it does not cope very well with the human problem of inconsistency. This is important bias which is present in human judgement and “the more alternatives and criteria in the evaluation process the more significant the inconsistency issue becomes″[13].…”

Section: The Choice Of Simulation Systemmentioning

confidence: 99%

Evaluating and Selecting Simulation Software Using the Analytic Hierarchy Process

Davis

Williams²

1994

Integrated Manufacturing Systems

101

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In order to be competitive and progress to a state of excellence in manufacture, companies are currently experiencing change. Decisions have to be made about the best way forward, and some insight into the possible outcomes is desirable. There is a small but growing awareness among British manufacturing companies that simulation could aid this insight, but potential users face the problem of evaluating and selecting from the many proprietary systems, the one which best matches their requirements at some preferred cost. Selection is made more difficult by continual updates and modifications to systems and by new software suppliers entering the market. Uses a research case study as the vehicle for proposing a framework for assessment and selection of simulation systems involving the use of the Analytic Hierarchy Process (AHP). Illustrates how this technique was used to make a system selection which matched a company′s selection criteria.

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Section: The Choice Of Simulation Systemmentioning

confidence: 99%

Evaluating and Selecting Simulation Software Using the Analytic Hierarchy Process

Davis

Williams²

1994

Integrated Manufacturing Systems

101

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show abstract

“…Examples of methods include scoring models, analytic hierarchy processes, techniques for order preference by similarity to ideal solution, outranking methods, goal programming models, stochastic methods, fuzzy MCDM methods, and life-cycle cost models. For applications, see, for example, Ghandforoush, Huang, and Taylor (1985), Imany and Schlesinger (1989), Sambasivarao and Deshmukh (1997), Wu (1999, 2000), Braglia and Gabbrielli (2000), Karsak (2002), Karsak andAhiska (2005, 2008), Amin and Emrouznejad (2007), Folgado, Pecas, and Henriques (2010), Kreng, Wu, and Wang (2011), Ghazinoory, Daneshmand-Mehr, and Azadega (2013), Oztaysi (2014), and Ren and Lutzen (2015).…”

Section: Cross-efficiencymentioning

confidence: 99%

Cross-efficiency for advanced manufacturing technology selection: A multi-task approach

Walheer

2022

RAIRO-Oper. Res.

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Advanced manufacturing technologies (AMTs) are more and more used by firms to perform repetitive tasks in the production processes. As opting for an ATM represents an important investment for firms, several methodologies have been suggested to help firm decision-makers selecting the best one. A popular concept in that context is the cross-efficiency technique. In short, it endogenously selects the best ATM by computing scores using linear programmings. In this paper, we extend the cross-efficiency technique by adding a new feature: we model ATMs as multi-task processes. The multi-task approach presents two main advantages. One, it naturally gives the option to allocate inputs/costs and indicators/attributes to every task, yielding to a more realist modelling of the AMT processes. Two, AMTs can be compared for every task separately, increasing the discriminatory power of the selection process. As a consequence, the overall performances can be better understood, and, in particular, the reasons for declaring a specific AMT to be best can be investigated. We demonstrate the usefulness of our approach by considering a numerical example and two applications. In each case, we demonstrate the practical and managerial usefulnesses of our approach.

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“…The model allows us to select one software architecture pattern from a given set of alternatives. Following (Ghandforoush et al 1985), for each software architecture pattern i an architecture evaluation measure AEM i is defined:…”

Section: Multi-criteria Evaluation and Decision Modelmentioning

confidence: 99%

An evaluation and decision method for ICT architectures for cross-organizational business process coordination

Roser¹,

Müller

Bauer

2010

Inf Syst E-Bus Manage

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Our work aims at providing support for the decision-making processes involved in the model-driven development of information technology (IT) solutions for cross-organizational business process (CBP) coordination and automation. The objective of the work described in this paper is to provide enterprise IT architects with an evaluation and decision model that enables the principled assessment and selection of an effective IT architecture paradigm (e.g. central broker, federated brokers, peer-to-peer) for a given cross-organizational business process coordination task. Our approach follows the principles of design science; the contribution of this paper is threefold: First, we present three common architectural patterns for (service-oriented) CBP coordination. Second, the core contribution is established by a new method for decision support suitable for IT architects to derive and evaluate an appropriate architecture paradigm for a given use case or application domain. The method is accompanied by a set of representative scenario descriptions that allow the evaluation and selection of appropriate IT system coordination architecture paradigms for CBP enactment, as well as a set of guidelines for how different contingencies influence IT system coordination architecture.

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A multi-criteria decision model for the selection of a computerized manufacturing control system

Cited by 18 publications

References 1 publication

Evaluating and Selecting Simulation Software Using the Analytic Hierarchy Process

Evaluating and Selecting Simulation Software Using the Analytic Hierarchy Process

Cross-efficiency for advanced manufacturing technology selection: A multi-task approach

An evaluation and decision method for ICT architectures for cross-organizational business process coordination

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