18,748 research outputs found

    Heuristic Solutions for Loading in Flexible Manufacturing Systems

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    Production planning in flexible manufacturing system deals with the efficient organization of the production resources in order to meet a given production schedule. It is a complex problem and typically leads to several hierarchical subproblems that need to be solved sequentially or simultaneously. Loading is one of the planning subproblems that has to addressed. It involves assigning the necessary operations and tools among the various machines in some optimal fashion to achieve the production of all selected part types. In this paper, we first formulate the loading problem as a 0-1 mixed integer program and then propose heuristic procedures based on Lagrangian relaxation and tabu search to solve the problem. Computational results are presented for all the algorithms and finally, conclusions drawn based on the results are discussed

    A decomposition-based algorithm for flexible flow shop scheduling with stochastic processing times

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    Best Student Paper Award of International Conference on Systems Engineering and Engineering Management 2009: Mr. Kai WangSince real manufacturing is dynamic and tends to suffer a wide range of uncertainties, research on production scheduling with uncertainty has received much more attention recently. Although various approaches have been investigated on the scheduling problem with uncertainty, this problem is still difficult to be solved optimally by any single approach, because of its inherent difficulties. This paper considers makespan optimization of a flexible flow shop (FFS) scheduling problem with stochastic processing times. It proposes a novel decomposition-based algorithm (DBA) to decompose an FFS into several clusters which can be solved more easily by different approaches. A neighbouring K-means clustering algorithm is developed to firstly group the machines of an FFS into an appropriate number of clusters, based on weighted cluster validity indices. A back propagation network (BPN) is then adopted to assign either the shortest processing time (SPT) or the genetic algorithm (GA) to generate a sub-schedule for each cluster. If two neighbouring clusters are allocated with the same approach, they are subsequently merged. After machine grouping and approach assignment, an overall schedule is generated by integrating the sub-schedules of the clusters. Computation results reveal that the proposed approach is superior to SPT and GA alone for FFS scheduling with stochastic processing times.postprintThe International Conference on Systems Engineering and Engineering Management 2009 of the World Congress on Engineering and Computer Science (WCECS 2009), San Francisco, CA., 20-22 October 2009. In Proceedings of WCECS, 2009, v. 2, p. 1050-106

    Organizational alternatives for flexible manufacturing systems

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    There is an increasing importance of different productive architectures related to worker involvement in the decision making, where is given due attention to the intuitive capabilities and the human knowledge in the optimization and flexibilization of manufacturing processes. Thus having reference point architecture of a flexible manufacturing and assembling system existent at UNINOVA-CRI, we will present some exploratory hypothesis about applicability of the concept of hybridization and its repercussions on the definition of jobs, in those organizations and in the formation of working teams.flexibility; robotics; work organization; manufacturing industry

    An improved cell controller for the aerospace manufacturing

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    The aerospace manufacturing industry is unique in that production typically focuses on high variety and quality but low volume. Existing flexible manufacturing cells are limited to certain types of machines, robots and cells which makes it difficult to introduce any changes. In this paper idea of treating machines, robots, any hardware and software as resource has been introduced. It describes the development of the Flexa Cell Coordinator (FCC), a system that is providing a solution to manage cells and their resources in a new flexible manner. It can control, organise and coordinate between cells and resources and is capable of controlling remote cells because of its distributed nature. It also provides connectivity with company systems e.g., Enterprise Resource Planner (ERP). It is extendable and capable of adding multiple cells inside the system. In FCC resources (e.g., tracker) can also be shared between cells. The paper presents its development and results of initial successful testing

    Enhanced cell controller for aerospace manufacturing

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    Aerospace manufacturing industry is unique in that production typically focuses on high variety and quality but extremely low volume. Manufacturing processes are also sometimes unique and not repeatable and, hence, costly. Production is getting more expensive with the introduction of industrial robots and their cells. This paper describes the development of the Flexa Cell Coordinator (FCC), a system that is providing a solution to manage resources at assembly cell level. It can control, organise and coordinate between the resources and is capable of controlling remote cells and resources because of its distributed nature. It also gives insight of a system to the higher management via its rich reporting facility and connectivity with company systems e.g., Enterprise Resource Planner (ERP). It is able to control various kinds of cells and resources (network based) which are not limited to robots and machines. It is extendable and capable of adding multiple numbers of cells inside the system. It also provides the facility of scheduling the task to avoid the deadlocking in the process. In FCC resources (e.g., tracker) can also be shared between cells

    MRP-based negotiation in customer-supplier relationship

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    In the present uncertain context, increasing the performance of the supply chains requires to define cooperative processes between partners aiming at providing a better answer to the final customer, with a risk shared between partners. Based on an analysis of real practices, we suggest in this communication to take the MRP process as a basis for defining what could be such a cooperative process
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