File Name: supply chain design and analysis models and methods .zip
The term supply chain modeling refers to different processes used over the years to define, determine and understand an organization's supply chain. It recognizes that there are many types of businesses, each of which has unique supply chain requirements.
The increased competition in the global market has obliged firms to maintain high customer service levels while at the same time, to reduce cost and maintain profit margins [ 1 ]. In this context, firms need to be able to produce and deliver a variety of customized products at low cost, high quality and short lead time [ 3 ], while possessing high reliability and flexibility to ever-changing requirements [ 4 ]. On the other hand, the competitiveness of a company is continuously tested and determined by its participation in networks of customers, distributors, partners and suppliers [ 5 ].
Its application demonstrates that this idea enables organizations to achieve higher quality products, better customer service, and lower inventory cost. In order to achieve high performance, supply chain functions must operate in an integrated and coordinated manner.
Several challenging problems associated with integrated supply chain design are: 1 how to model and coordinate the supply chain business processes, specifically in the area of supply chain workflows; 2 how to analyze the performance of an integrated supply chain network so that optimization techniques can be employed to improve customer service and reduce inventory cost; and 3 how to evaluate dynamic supply chain networks and obtain a comprehensive understanding of decision-making issues related to supply network configurations.
These problems are most representative in the supply chain theory's research and applications. There are three major objectives for this research. The first objective is to develop viable modeling methodologies and analyzing algorithms for supply chain business processes so that the logic properties of supply chain process models can be analyzed and verified.
This problem has not been studied in integrated supply chain literature to date. To facilitate the modeling and verification analysis of supply chain workflows, an object-oriented Petri nets based modular modeling and analyzing approach is presented.
The proposed, structured, process-modeling algorithm provides an effective way to design structured supply chain business processes. The second objective is to develop a network of inventory-queue models for the performance analysis and optimization of an integrated supply network with inventory control at all sites. An inventory-queue is a queueing model that incorporates an inventory replenishment policy for the output store. This dissertation extends the previous work done on the supply network model with base-stock control and service requirements.
Instead of one-for-one base stock policy, batch-ordering policy and lot-sizing problems are considered. To determine the replenishment lead times of items at the stores, a fixed-batch target-level production authorization mechanism is employed to explicitly obtain performance measures of the supply chain queueing model. The validity of the proposed model is illustrated by comparing the results from the analytical performance evaluation model and those obtained from the simulation study.
The third objective is to develop simulation models for understanding decision-making issues of the supply chain network configuration in an integrated environment. Simulation studies investigate multi-echelon distribution systems with installation stock reorder policy and echelon stock reorder policy.
The results show that, depending on the structure of multi-echelon distribution systems, either echelon stock or installation stock policy may be advantageous. This dissertation presents a new transshipment policy, called "alternate transshipment policy," to improve supply chain performance.
In an integrated supply chain network that considers both the distribution function and the manufacturing function, the impacts of component commonality on network performance are also evaluated.
The results of analysis-of-variance and Tukey's tests reveal that there is a significant difference in performance measures, such as delivery time and order fill rates, when comparing an integrated supply chain with higher component commonality to an integrated supply chain with lower component commonality. Several supply chain network examples are employed to substantiate the effectiveness of the proposed methodologies and algorithms.
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Despite the increasing interest in supply chain management SCM by researchers and practitioners, there is still a lack of academic literature concerning topics such as methodologies to guide and support SCM evaluation. Most developed methodologies have been provided by consulting companies and are restricted in their publication and use. We analyze the applicability of the proposed model based on findings from interviews with experts - academics and practitioners - as well as from case studies of three focal firms and their supply chains. In general terms, the methodology can be considered a diagnostic instrument that allows companies to evaluate their maturity regarding SCM practices. From this diagnosis, firms can identify and implement activities to improve degree of adherence to the reference model and achieve SCM benefits.
The supply chain in Fig. 1 consists of five stages. Generally, multi-stage models for supply chain design and analysis can be divided into four categories, by the.
A literature review and gap analysis indentifies key limitations of industry best practice when modelling of supply chains. To address these limitations the paper reports on the conception and development of an integrated modelling methodology designed to underpin the analytical design of complex supply chains. The methodology is based upon a systematic deployment of EM, CLD, and SM techniques; the integration of which is achieved via common modelling concepts and decomposition principles. Guidelines for the application of each step of the methodology are described. Also described are recommended data collection methods and expected modelling outcomes for each step. The paper reflects on preliminary benefits gained during industry based case study modelling and identifies areas of potential improvement.
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Внутри не было никакого лирджета. Он несколько раз моргнул затуманенными глазами, надеясь, что это лишь галлюцинация. Увы, ангар был пуст. О Боже. Где же самолет.
Данные? - спросил Бринкерхофф. - Какие такие данные. Танкадо отдал кольцо.
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