795 resultados para Supply Chain Simulation, Incomplete Datasets, Variable Cycle Times


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This paper examines a large structural component and its supply chain. The component is representative of that used in the production of civil transport aircraft and is manufactured from carbon fibre epoxy resin prepreg, using traditional hand layup and autoclave cure. Life cycle assessment (LCA) is used to predict the component’s production carbon emissions. The results determine the distribution of carbon emissions within the supply chain, identifying the dominant production processes as carbon fibre manufacture and composite part manufacture. The elevated temperature processes of material and part creation, and the associated electricity usage, have a significant impact on the overall production emissions footprint. The paper also demonstrates the calculation of emissions footprint sensitivity to the geographic location and associated energy sources of the supply chain. The results verify that the proposed methodology is capable of quantitatively linking component and supply chain specifics to manufacturing processes and thus identifying the design drivers for carbon emissions in the manufacturing life of the component.

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Coordination among supply chain members is essential for better supply chain performance. An effective method to improve supply chain coordination is to implement proper coordination mechanisms. The primary objective of this research is to study the performance of a multi-level supply chain while using selected coordination mechanisms separately, and in combination, under lost sale and back order cases. The coordination mechanisms used in this study are price discount, delay in payment and different types of information sharing. Mathematical modelling and simulation modelling are used in this study to analyse the performance of the supply chain using these mechanisms. Initially, a three level supply chain consisting of a supplier, a manufacturer and a retailer has been used to study the combined effect of price discount and delay in payment on the performance (profit) of supply chain using mathematical modelling. This study showed that implementation of individual mechanisms improves the performance of the supply chain compared to ‘no coordination’. When more than one mechanism is used in combination, performance in most cases further improved. The three level supply chain considered in mathematical modelling was then extended to a three level network supply chain consisting of a four retailers, two wholesalers, and a manufacturer with an infinite part supplier. The performance of this network supply chain was analysed under both lost sale and backorder cases using simulation modelling with the same mechanisms: ‘price discount and delay in payment’ used in mathematical modelling. This study also showed that the performance of the supply chain is significantly improved while using combination of mechanisms as obtained earlier. In this study, it is found that the effect (increase in profit) of ‘delay in payment’ and combination of ‘price discount’ & ‘delay in payment’ on SC profit is relatively high in the case of lost sale. Sensitivity analysis showed that order cost of the retailer plays a major role in the performance of the supply chain as it decides the order quantity of the other players in the supply chain in this study. Sensitivity analysis also showed that there is a proportional change in supply chain profit with change in rate of return of any player. In the case of price discount, elasticity of demand is an important factor to improve the performance of the supply chain. It is also found that the change in permissible delay in payment given by the seller to the buyer affects the SC profit more than the delay in payment availed by the buyer from the seller. In continuation of the above, a study on the performance of a four level supply chain consisting of a manufacturer, a wholesaler, a distributor and a retailer with ‘information sharing’ as coordination mechanism, under lost sale and backorder cases, using a simulation game with live players has been conducted. In this study, best performance is obtained in the case of sharing ‘demand and supply chain performance’ compared to other seven types of information sharing including traditional method. This study also revealed that effect of information sharing on supply chain performance is relatively high in the case of lost sale than backorder. The in depth analysis in this part of the study showed that lack of information sharing need not always be resulting in bullwhip effect. Instead of bullwhip effect, lack of information sharing produced a huge hike in lost sales cost or backorder cost in this study which is also not favorable for the supply chain. Overall analysis provided the extent of improvement in supply chain performance under different cases. Sensitivity analysis revealed useful insights about the decision variables of supply chain and it will be useful for the supply chain management practitioners to take appropriate decisions.

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Supply chain management has emerged as a popular and useful concept in the construction industry and research community since the mid 1990s. Research in construction supply chain management draws from a broad range of disciplines, notably: (1) Industrial organization economics to better understand market structure and forces and their effect on firm and supply chain behavior and (2) Analytic modeling of supply chains to improve supply chain performance along metrics such as speed, cost, reliability, quality, etc. Both industrial organization and analytic modeling provide useful but ultimately incomplete perspectives and prescriptions for construction supply chain management. As such, this paper proposes development of an interdisciplinary research agenda that draws from both fields. Towards that agenda, a review of research is presented to introduce the main ideas, relevant literature, and theory and methods in each of the two areas. From these independent reviews, applications that could benefit from a combined perspective are identified and used as a basis for development of an interdisciplinary research agenda.

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Supply chain management has emerged as a popular and useful concept in the construction industry and research community since the mid 1990s. Research in construction supply chain management draws from a broad range of disciplines, notably: (1) industrial organization economics to better understand market structure and forces and their effect on firm and supply chain behavior and (2) Analytic modeling of supply chains to improve supply chain performance along metrics such as speed, cost, reliability, quality, etc. Both industrial organization and analytic modeling provide useful but ultimately incomplete perspectives and prescriptions for construction supply chain management. As such, this paper proposes development of an interdisciplinary research agenda that draws from both fields. Towards that agenda, a review of research is presented to introduce the main ideas, relevant literature, and theory and methods in each of the two areas. From these independent reviews, applications that could benefit from a combined perspective are identified and used as a basis for development of an interdisciplinary research agenda.

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Supply chains are complex adaptive systems for which final performance depends upon numerous interdependent decisions made by numerous firms which synthesise inputs from various resources systems.  The dynamic interdependent behaviour of social, economic, material and informational resource systems within eco-industrial settings that support the built environment life cycle supply chains can be studied at the supply chain level.  The impact of megaprojects is significant and holds promise to explore the impact of decisions on various systems as it combines project and system boundaries.  Megaoprojects considered as major events within systems can produce critical revolutionary impacts on the systems within which they are embedded.  The decisions that are made on megaprojects are central to risk management.  typically major infrastructure projects are procured through a form of public private partnership (PPP).  The core principle of PPP is value for money which refers to the best available outcome attempting to take account of all benefits, costs and risks over the whole life of the procurement.  In this paper the focus is on Australia where there has been considerable acitivity in the use of PPPs.  With recent national infrastucture packages proposed to stimulate the economy due to the global financial crisis, decision modelling on risks is a revelant and critical matter not only in practice but also in the research community.  PPPs encourage the whole-of-lifecycle approach in the procurement and management of public sector assets by transparently recognising the costs and risks associated with the whole life of the required service or facility, thus integrated whole of life supply chains can be considered.  By creating a single point of responsibility for an entire project from inception through operation, a strong incentive is created for thinking about the effects that a design or construction decision will have on the effectiveness and efficiency of managing and maintaining a facility during its operational life.  The decision to procure holistic supply chains becomes a much more viable commercial reality in the PPP environment than previously considered in the usual commercial construction spot transactional approach.  These types of decisions tend to be imprecise, approximate and complex requireing justification and reasoning logic rather than the classical 'truth' logic.  The purpose of this paper is to develop a theoretical decision framework which combines interdependency and multi-values logic for supply chain procurement modelling.

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Supply chain management has emerged as a popular and useful concept in the construction industry and research community since the mid 1990s. Research in construction supply chain management draws from a broad range of disciplines, notably: (1) industrial organization economics to better understand market structure and forces and their effect on firm and supply chain behavior and (2) Analytic modeling of supply chains to improve supply chain performance along metrics such as speed, cost, reliability, quality, etc. Both industrial organization and analytic modeling provide useful but
ultimately incomplete perspectives and prescriptions for construction supply chain management. As such, this paper proposes development of an interdisciplinary research agenda that draws from both fields. Towards that agenda, a review of research is presented to introduce the main ideas, relevant literature, and theory and methods in each of the two areas. From these independent reviews, applications that could benefit from a combined perspective are identified and used as a basis for development of an
interdisciplinary research agenda.

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The real world challenges of incomplete information access and bounded computational resources in supply chain management motivate us to propose a bottom up approach to supply chain intelligence, built over a widely used reactive card-based replenishments system (kanban). The rationale is to use agent technology to improve the performance of the traditional kanban system while maintaining its recognized usability. Instead of optimizing a system utility function, we encode the system goal in desired behaviours of individual agents that reason about their own behaviours in the local context. This paper discusses a rigorous framework for evaluation of the proposal based on the concept of benchmarking. Preliminary results from these simulations show remarkable improvements over the traditional system. Furthermore, use of the benchmarking framework gives confidence that these results translate into real performance gains in practical implementations.

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Australia has adopted public-private partnership (PPP) as a major strategy for procuring infrastructure for decades. However, even though considered to be a mature and sophisticated market, several major
failures have occurred resulting in increasing financial burdens on taxpayers. Failures have typically been traced back to economic evaluation and, in particular, value-for-money across the supply chain
in the original proposal. However, the literature review identified that there was no economic model that evaluated holistically the transaction costs of PPPs across the supply chain. In this paper, theories of transaction cost economics and construction supply chain economics are critiqued and analysed in order to develop a strategic infrastructure procurement evaluation model. The model will offer decision makers with an insight into project life cycle economic outcomes needed to successfully deliver PPPs.

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The objective of this article is to analyse how green supply chain management (GSCM) practices are being adopted by some high-tech companies located in Brazil. The research was conducted using the case study approach, focusing on eight companies that are representative of this sector. The main results are: (a) the most adopted GSCM practices in the studied high-tech companies located in Brazil are internal environmental management, investment recovery and reverse logistics and (b) Brazilian environmental legislation and international policies are very important in driving the adoption of GSCM practices. The internationalisation of companies was also found to be a variable that interferes with the adoption of GSCM practices. This is one of the first studies that examine the relationship between GSCM and the internationalisation of companies located in Brazil. © 2013 Springer-Verlag London.

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Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

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Da sich Additive Manufacturing (AM) von traditionellen Produktionsverfahren unterscheidet, entstehen neue Möglichkeiten im Produktdesign und im Supply Chain Setup. Die Auswirkungen der Aufhebung traditionellen Restriktionen im Produktdesign werden unter dem Begriff „Design for Additive Manufacturing“ intensiv diskutiert. In gleicher Weise werden durch AM Restriktionen im traditionellen Supply Chain Setup aufgehoben. Insbesondere sind die folgenden Verbesserungen möglich: Reduktion von Losgrössen und Lieferzeiten, bedarfsgerechte Produktion auf Abruf, dezentrale Produktion, Customization auf Ebene Bauteil und kontinuierliche Weiterentwicklung von Bauteilen. Viele Firmen investieren nicht selbst in die AM Technologien, sondern kaufen Bauteile bei Lieferanten. Um das Potential der AM Supply Chain mit Lieferanten umzusetzen, entstehen die folgenden Anforderungen an AM Einkaufsprozesse. Erstens muss der Aufwand pro Bestellung reduziert werden. Zweitens brauchen AM Nutzer einen direkten Zugang zu den Lieferanten ohne Umweg über die Einkaufsabteilung. Drittens müssen geeignete AM Lieferanten einfach identifiziert werden können. Viertens muss der Wechsel von Lieferanten mit möglichst geringem Aufwand möglich sein. Ein mögliche Lösung sind AM spezifische E-Procurement System um diese Anforderungen zu erfüllen

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This paper reports on the development of elements of an e-supply chain management system for managing maintenance, repair and overhaul (MRO) relationships in the aerospace industry. A standard systems development methodology has been followed to produce a process model (i.e. the AMSCR model); an information model (i.e. business rules) and a computerised information management capability (i.e. automated optimisation). The proof of concept for this web-based MRO supply chain system has been established through the collaboration with a sample of the different types of supply chain members. The proven benefit is a reduction in the stock-holding costs for the whole supply chain whilst also minimising non-flying time of the aircraft that the supply chain supports. This type of system is now vital in an industry that has continuously decreasing profit margins, which in turn means pressure to reduce servicing times and increase the interval between maintenance actions.

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Supply chains are advocated widely as being the new units for commercial competition and developments have made the sharing of supply chain wide information increasingly common. Most organisations however still make operational decisions intended to maximise local organisational performance. With improved information sharing a holistic focus for operational decisions should now be possible. The development of a pan supply chain performance framework requires an examination of the conditions under which holistic-decisions provide benefits to either the individual enterprise or the complete supply chain. This paper presents the background and supporting methodology for a study of the impact of an overall supply chain performance metric framework upon local logistics decisions and the conditions under which such a framework would improve overall supply chain performance. The methodology concludes a simulation approach using a functionally extended Gensym's e-SCOR model, together with case based triangulation, to be optimum. Copyright © 2007 Inderscience Enterprises Ltd.

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This paper proposes a conceptual model for a firm's capability to calibrate supply chain knowledge (CCK). Knowledge calibration is achieved when there is a match between managers' ex ante confidence in the accuracy of held knowledge and the ex post accuracy of that knowledge. Knowledge calibration is closely related to knowledge utility or willingness to use the available ex ante knowledge: a manager uses the ex ante knowledge if he/she is confident in the accuracy of that knowledge, and does not use it or uses it with reservation, when the confidence is low. Thus, knowledge calibration attained through the firm's CCK enables managers to deal with incomplete and uncertain information and enhances quality of decisions. In the supply chain context, although demand- and supply-related knowledge is available, supply chain inefficiencies, such as the bullwhip effect, remain. These issues may be caused not by a lack of knowledge but by a firm's lack of capability to sense potential disagreement between knowledge accuracy and confidence. Therefore, this paper contributes to the understanding of supply chain knowledge utilization by defining CCK and identifying a set of antecedents and consequences of CCK in the supply chain context.