Process Modeling for Simulation

This paper discusses shortfalls in relation to the requirements gathering phases of simulation. While many developments have taken place around supporting the model coding task of simulation, there are few tools available to assist in the requirements gathering phase. This is surprising as it has been reported by several researchers that the requirements phase can absorb twice as much resources as the coding phase. There are numerous process modeling tools available (over 100) that can and have been used to support the requirements phase of simulation. This paper provides a selective review of some of the most important in relation to simulation. A conclusion from this review is that none of the tools available adequately supports the requirements gathering phase of simulation. It is proposed that a process modeling tool be developed specifically to support simulation requirements gathering. The design objectives in the development of the tool are: (1) it should be capable of capturing a detailed description of a discrete event system; (2) it should have a low modeling burden and therefore be capable of being used by non-specialists; (3) it should present modeling information at a high semantic level so that manufacturing personnel can rationalize with it; (4) it should have good visualization capabilities; (5) it should support project teamwork. Based on these design objectives a proposed simulation process modeling tool called simulation activity diagrams (SAD) is presented

Developing retailer selection factors for collaborative planning, forecasting and replenishment

Purpose– Selecting an appropriate partner is a vital and strategic decision-making process in any supply chain collaboration initiative. The purpose of this study is to introduce and explore the key factors considered by manufacturers in the selection of an appropriate retailer(s) for Collaboration and Collaborative Planning, Forecasting and Replenishment (CPFR) implementation and the relationships between these factors. Design/methodology/approach– A comprehensive literature review and experts’ views are applied to identify the main retailer selection and evaluation factors for CPFR implementation. A Fuzzy DEMATEL approach is then used to rank and analysis the interaction among identified factors. The findings are finally evaluated using a case study from a high-tech industry. Findings– The most important partner selection factors comprising of five dimensions and 24 factors are introduced. Of the identified criteria, three factors: manufacturer’s familiarity with the retailer, workforce skills and training and customer service orientation and capability have been identified as critical when selecting retailers for CPFR implementation. The technological capabilities dimensions are identified as the only net cause dimension which affects all other dimensions and its importance and role in simplifying and enhancing the speed and flexibility of CPFR implementation. Practical implications– The study identifies practical retailer selection factors for CPFR implementation and the causal relationships between factors. Developed retailer selection dimensions and criteria will assist manufacturers and retailers in understanding the role these factors play in CPFR implementation. This will also assist in appropriate retailer(s) selection by manufacturers. Originality/value– This study contributes to the literature on CPFR and tackles the important issue of selecting appropriate partners by developing retailer selection dimensions and criteria in CPFR implementation

ISM analysis of CPFR implementation barriers

Collaborative Planning, Forecasting and Replenishment (CPFR) as an interconnection scheme between organizations has been shown to have significant benefits. Since its inception in the 1990s, its uptake has been lower than originally predicted. This paper identifies the major barriers and their interrelationships in CPFR implementations with a focus on high-tech industries. Interpretive Structural Modeling (ISM) is used with a group of CPFR experts from industry/academia and Matrice d’Impacts Croisés Multiplication Appliquée àun Classement (MICMAC) analysis to identify the driving and dependence powers. The paper identified 45 CPFR barriers and classifies them into four categories based on expert opinion, with only 13 of these determined to be significant. The results indicate that in terms of categories, managerial barriers are a significant root cause for both process and cultural barriers and CPFR implementation difficulties. It also indicates that although the importance of information technology to launch collaborative schemes has been addressed by many scholars, technology alone is not the complete solution for successful CPFR implementation. The paper has significant practical implications for organizations as it identifies the main CPFR barriers and their causal relationships. This will help firms in the process of CPFR strategy development particularly for mitigation strategies for dominant barriers

A simulation based supply partner selection decision support tool for service provision in Dell.

Partner selection is an important aspect of all outsourcing processes. Traditional partner selection, typically involves steps to determine the criteria for outsourcing, followed by a qualification of potential suppliers and concluding with a final selection of partner(s). Reverse auctions (RAs) have widely been used for partner selection in recent times. However, RAs, although proven successful in initial price reduction strategies for product and service provision, can suffer from reduced effectiveness as the number of executions increases. This paper illustrates Dell’s experience of such diminishing returns for its outsourced after sales product repair service and presents the development, of a new partner selection methodology which incorporates a new process improvement stage to be executed in combination with the final selection phase. This new methodology is underpinned by the development of a computer based simulation supply partner selection decision support tool for service provision. The paper highlights the significant additional cost saving benefits achievable and improvement in service through the use of advanced simulation based decision supports

A framework for collaborative planning, forecasting and replenishment (CPFR): state of the art

Purpose– Although many papers purport the significant value attributable to supply chain performance from the use of Collaborative Planning, Forecasting and Replenishment (CPFR), the question of ‘what are the main constructs and efficient framework for successful implementation of CPFR?’ remains largely unanswered. This question will be addressed by identifying and analysing the main constructs for successful implementation of CPFR. This paper attempts first to seek answers to this question. Second, to review the scope and value of CPFR using a devised state-of-the-art taxonomy for the classification of selected bibliographical references and third, to develop a conceptual framework by identifying areas which need more research. Design/methodology/approach– The method underlying this paper followed the steps of a systematic literature review process outlined by Soni and Kodali (2011). The review is based on a total of 93 papers published from 1998 to 2013 on CPFR. Findings– Four main constructs for successful implementation of CPFR have been identified: CPFR enablers, CPFR barriers, trading partner selection and incentive alignment. The findings indicate that there is a need for better understanding of the amount and level of information sharing as an important function of CPFR implementation. The paper also illustrates a number of shortcomings in the current literature and provides suggestions to guide future research on implementing CPFR in different industries. Practical implications– This paper is of interest to both academicians and practitioners as it helps to better understand the concept and role of CPFR in supply chain integration and its implementation results, enablers and inhibitors. The proposed framework in this paper can be used to give insight for future research and practice. Originality/value– The paper offers a framework for the review of previous research on CPFR and identifies the most important shortcomings that need to be addressed in future research. In addition, this review is both greater in scope than previous reviews and is broader in its subject focus

Requirements Gathering for Simulation

This paper discusses the current shortfalls in support for the pre-coding phases of a discrete event simulation project. The paper then presents a process modelling technique, Simulation Activity Diagrams (SADs), developed to specifically support the initial requirements gathering phases of a simulation project. The paper concludes with an outline of proposed future developments to the modelling technique

Simulation Activity Diagrams

This paper presents a technique, Simulation Activity Diagrams (SAD), developed to lessen the modelling burden during the initial requirements gathering phases of a simulation project. The technique also allows the capture and visual communication of detailed information, to manufacturing personnel, which may otherwise be lost in detailed programming code

Process Modelling Support for the Conceptual Modelling Phase of a Simulation Project

While many developments have taken place around supportingthe model coding task of simulation, there are few toolsavailable to assist in the conceptual modelling phase. Severalauthors have reported the advantages of using processmodelling tools in the early phases of a simulation project.This paper provides an overview of process modelling toolsin relation to their support for simulation, categorizing thetools into formal method and descriptive methods. A conclusionfrom this review is that none of the tools availableadequately support the requirements gathering phase ofsimulation. This is not surprising as none of the processmodelling tools were developed for explicit support of simulation.The paper then presents results of research intodeveloping a new process modelling method for simulation