Research On The Logistics Balance Of Mixed Integrated Virtual Enterprise Based On TOC

With the globalization and marketing of economic, the competitions betweencorporations are becoming more and more stinging. So, most of the Small&Medium-sized Enterprises (SME) are facing new challenges. SME always exist inclusters. How to stay core competitiveness and stand out in the clusters is the key tothe development of SME. The appearance of Virtual Enterprise which can solve theproblems in lacking funds and resources etc. of SME is an effective organizationmode to the development of SME. Logistics which is the third profit resource ofenterprises is also important to Virtual Enterprises. Production logistics is animportant part of enterprise logistics, and it should never be neglected. This paper isrelied on The State Plan for Soft Science “Virtual Organization of Small&Medium-sized Enterprises”（2009GXSZK027）,and production logistics balanceof Mixed Integrated Virtual Enterprise is a masterstroke. Based on the characters ofMixed Integrated Virtual Enterprises, the model of production logistics system has been created. Then the problems of production logistics bottleneck shiftingprobability as well as production balance have been studied systematically. In thestudy, the ways such as Grey Theory, Maximum Entropy Principle, GeneticAlgorithms, Analytic Hierarchy Process and Matlab are applied to resolve questions.Finally, the ways are applied to a virtual enterprise of plastic injection moldingmachine in Ningbo.In this article, the component elements of virtual enterprise productionlogistics system are analyzed and the similarities and differences between the singleenterprise and virtual enterprise are compared at first. Then network graph is used tocreate production logistics system model. This network model is from the totalmodule to process module, so, the component elements of production logistics areperfectly clear. Every production logistics chain is known clearly. This is thebasement of continue researches.TOC pursue logistics balanced. To achieve this aim, bottleneck must beidentified first. The second part of this paper research on the bottleneck shiftingprobability of production logistics. This part analyzes and classifies the bottleneckshifting factors first, then selects two of the most typical as examples to forecasttheir time distribution by using Grey Theory and Maximum Entropy Principle.Finally, bottleneck shifting probability model is created by using some knowledgeabout Mathematical Statistics. The result of this part can forecast the trend in bottleneck shifting effectively, and it also provides a new method and idea todynamically identify bottlenecks.At last, this paper study on the problem of production logistics balance basedon identifying the bottleneck. This study is mainly on balancing the lot-sizing tomake logistics balance. Lot-sizing is divided into two parts—process batch size(PBS) and transfer batch size (TBS). And it is divided into three different sizes bythe bottleneck. Multi-objective optimization model based on production logisticsbalance, shortest time and lowest cost is established. Then using Analytic HierarchyProcess to determine every single objective’s weight, and take numerical exampleinto it, finally, obtain the optimum lot-sizing by using Genetic Algorithms. Theresult show that the lot-sizing under this model not only make logistics balance, butalso make the preparation and transportation time and cost ratio low to the total costand time. It has a real sense for reducing unnecessary waste in practical production.