251 research outputs found

    Mixed-integer linear programming approach to U-line balancing with objective of achieving proportional throughput per worker in a dynamic environment

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    One of the major challenges of manufacturing companies is to remain competitive in a very dynamic environment dictated by fluctuations in production rate and customer demand. These challenges may be attributed to frequent changes in customer expectations, unsteady economic conditions or failure to reach the projected throughput due to inefficiencies in production systems. Survival in such a dynamic environment is contingent on implementing manufacturing systems that are able to adapt to change quickly and economically. The U-Shaped production cell is considered to be one of the most flexible techniques for changing the number of workers in the cell to match cell cycle time to planned cycle time. However, companies currently use a trial-and-error method to develop walk-paths. It is a very iterative and time consuming process that does not always guarantee an optimal solution. Walk-paths need to be performed for all possible number of workers. Fluctuations are adapted to by altering only the number of workers and the worker’s walk-path without changing the number of stations and task allocations. Selecting the best configuration (i.e. optimal number of stations and task allocation) is dependant upon the linearity metric i.e. the measurement of the proportional throughput per worker. Designing the production cell by considering the linearity helps to keep direct labor costs per unit at a minimum for any number of workers employed. This thesis proposes a mixed integer linear model for U-shaped lines that determines the best cell configuration for various number of workers with the objective function of achieving proportional throughput per worker and decreasing the iteration time. The problem originated at Delphi Corporation but has been generalized to be applicable to other Lean systems. The model has been constructed using OPL Studio 3.7

    Ant colony optimization for the single model U-type assembly line balancing problem

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    Cataloged from PDF version of article.An assembly line is a production line in which units move continuously through a sequence of stations. The assembly line balancing problem is defined as the allocation of tasks to an ordered sequence of stations subject to precedence constraints with the objective of optimizing a performance measure. In this paper, we propose ant colony algorithms to solve the single-model U-type assembly line balancing problem. We conduct an extensive experimental study in which the performance of the proposed algorithm is compared against best known algorithms reported in the literature. The results indicate that the proposed algorithms display very competitive performance against them. & 2009 Elsevier B.V. All rights reserved

    A Novel Work-Sharing Protocol for U-Shaped Assembly Lines

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    Companies worldwide try to employ contemporary manufacturing systems that can cope with changes in external competitive environments and internal process variability. Just In Time (JIT) philosophy helps achieve the required resilience by its policy of having people, machines, and material just-in-time for any given process. U-shaped assembly lines (U-lines) are used to implement JIT principles. Another principle that helps achieve competitive advantage by developing a flexible workforce that responds efficiently to change is that of work-sharing. Operators share work and help each other in a dynamic and floating way, requiring little management effort to distribute workload amongst operators, or balance the assembly line. The aim of this work is to develop an effective work-sharing protocol for U-shaped assembly lines that will provide the combined advantages of U-lines and work-sharing principles. The new protocol is based on two ideas from literature - the Cellular Bucket Brigade (CBB) system, and the Modified Work-Sharing (MWS) system. To keep the focus on developing the protocol, the scope of this work was limited to two worker systems. The methodology used is to model the protocol and U-line system as a discrete event simulation model, and then use an optimization model to maximize throughput and find optimal buffer locations and levels. A physical simulation experiment was conducted in the Toyota Production Systems lab at RIT to validate the model. Once validated, computer simulation experiments were run with industry data, and results obtained were compared with existing protocols from literature. It was found that the new protocol performed at least as well as the CBB protocol, improving the output by an average of 1%, for the scenarios tested. Increase in processing speed variability as well as larger variation among workers were found to negatively impact the performance of the protocol. The results were analyzed further to understand why these factors are significant, and why there are anomalies and patterns, or lack thereof. Finally, limitations of the protocol, and opportunities for future research in the field are presented. Major limitations of the protocol are that it is difficult to comprehend, and the assumption of an assembly line divided into equal tasks is not practical in the industry

    The Impact of Walking Time on U-Shaped Assembly Line Worker Allocation Problems

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    The one-piece flow manufacturing line of single and customized products is usually organized as a U-shaped assembly layout. In this study, the characteristics of a single U-line are described and modeled. The worker allocation problem is hierarchically concerned with the task assignment into a U-line and allocate task to workers in sequence. Several products are assembled in 7-task to 297-task problems, and each problem is performed with a given cycle time. The primary purpose is to identify the impact of walking time on both symmetrical and rectangular U-shaped assembly layouts. The minor purpose is to compare the number of workers between two fixed layouts. Coincidence algorithm demonstrates clarifying solutions. To respond to two previous aims, the primary objective function of a number of workers is used. Finally, with the Pareto-optimal frontier between the deviation of operation times of workers and the walking time, its computational study is exemplified to identify good task assignment and walking path

    Ant colony optimization for the single model U-type assembly line balancing problem

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    Cataloged from PDF version of article.The assembly line is a production line in which units move continuously through a sequence of stations. The assembly line balancing problem is the allocation of tasks to an ordered sequence of stations subject to the precedence constraints with the objective of minimizing the number of stations. In a U-line the line is configured into a U-shape topology. In this research, a new heuristic, Ant Colony Optimization (ACO) meta-heuristic, and its variants are proposed for the single model U-type assembly line balancing problem (UALBP). We develop a number of algorithms that can be grouped as: (i) direct methods, (ii) modified methods and (iii) methods in which ACO approach is augmented with some metaheuristic. We also construct an extensive experimental study and compare the performance of the proposed algorithms against the procedures reported in the literature.Alp, ArdaM.S

    The Journal of ERW and Mine Action Issue 14.3 (2010)

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    Focus: Looking Beyond Mine Action | Feature: Development and Funding | Special Report: Update on National Programs | Notes from the Field | Research & Developmen

    The BG News November 7, 1984

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    The BGSU campus student newspaper November 7, 1984. Volume 67 - Issue 41https://scholarworks.bgsu.edu/bg-news/5317/thumbnail.jp

    Human Resources for Health: Overcoming the Crisis: Joint Learning Initiative

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    Presents findings and recommendations of the Joint Learning Initiative to identify strategies for healthcare workforce development in developing countries. Calls for action that engages workers, communities, national leadership, and global responsibility
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