Dooyoung Shin

Simultaneous formation of machine and human cells in group technology : a multiple objective approach

Since the advent of group technology (GT) as a primary manufacturing tool for reducing setup times and improving production efficiencies, its central theme has been the grouping of similar parts into part families and machines into machine cells. Although the formation of machine-part manufacturing cells is the essence of GT, its full benefits cannot be gained without forming ‘human’ cells in such a way that machine operators with similar expertise and skills are brought together to produce similar part families. Nevertheless, much of the existing GT literature overlooks the behavioural issues associated with a group of workers in the machine cell. This paper addresses such issues by simultaneously forming both machine and compatible human cells. In so doing, we develop a multiple objective model that enables us to analyse the tradeoff between economic and behavioural benefits.

An efficient heuristic for solving stochastic assembly line balancing problems

Abstract This paper investigates the problem of assigning tasks to work stations in assembly lines when there exists variability in processing assembly tasks. For such a stochastic assembly line balancing problem, an efficient heuristic is developed based on the fact that there is a feasible cycle time at which the expected total cost (the sum of normal operating cost and incompletion cost) becomes a minimum. The heuristic provides an optimal task assignment with such a cycle time. The heuristic also searches for a proper work allowance at each work station for any given cycle time and variability, and suggests an appropriate task allocation.

Uniform Assembly Line Balancing with Stochastic Task Times in Just‐in‐time Manufacturing

Recognising the enormous potential of just‐in‐time (JIT) concepts for boosting productivity and quality, an increasing number of US and European firms consider adopting JIT concepts in manufacturing. However, the transfer of a manufacturing policy from traditional to JIT always requires radical structural changes in a production line design. One typical example of these changes is uniform assembly which does not allow high variability in the production schedules. Consequently, major hindrance to uniform assembly is a random fluctuation of task processing times in assembly line balancing. This article proposes a heuristic which takes into account stochastic task processing times and further develops a work assignment with the lowest expected total cost as well as an assignment with the highest work completion probability crucial for the success of JIT manufacturing.

An analysis of line‐stop strategy in just‐in‐time manufacturing

In pursuit of zero‐defect quality, a growing number of JIT manufacturing firms often consider a line‐stop strategy that allows workers to stop the assembly line when abnormalities occur during production process, and to repair defects immediately as they occur. The line‐stop strategy contrasts with a traditional off‐line repair strategy that either scraps the defects or sends them to a separate repair station. Develops an expected total cost model to demonstrate the cost‐effectiveness of the line‐stop strategy over the off‐line repair strategy in JIT environments. Computational experiments indicate that cost savings resulting forum using the line‐stop strategy are greater than those using the off‐line repair strategy.

On the effectiveness of on‐line repair policy: quality failure costs perspective

Examines the effectiveness of the line‐stop (on‐line) repair policy over traditional off‐line repair policy through two mathematical models developed based on total quality failure costs (TFC). The proposed models demonstrate that the TFC framework can be a valuable performance measure for evaluating the contribution of the line‐stop repair policy. The computational results also show that the line‐stop policy can bring substantial savings over the off‐line repair policy.

Network Analysis for Active and Passive Propagation Models

A large number of studies have been conducted over a long period of time to better understand how people adopt new products and/or ideas. With recent advancement in social network technologies such as Facebook and Twitter, the interest in better understanding the role of social network effect or social influence on the adoption of an idea has again been brought to the forefront. In this study, we examine the propagation of ideas through a social network and we introduce two network propagation rules to explain the idea propagation under social influence. We then apply the rules to different network models, which include a large-world network, a smallworld network, a random network, and local neighbor networks such as a path, a star, and their variations. In terms of social network in our study, we say that if a person has adopted an idea, then the person is infected by the idea. So the main interest of our study is to find the minimum number of initially infected individuals (i.e., early adopters of an idea) to effectively infect the rest of the social network. Furthermore, we give examples of real-world situations in management and the spread of violence, where the proposed propagation analysis can be applied.

Assuring quality at the source with varying worker skills: economic justification of the online repair policy

Traditionally, quality control on an assembly line has been conducted by quality inspectors at the end of the assembly line. Defective or incomplete parts identified during the production cycle are typically transferred to a separate repair shop where such parts are reworked, retested, re-inspected or replaced. In contrast, todays repetitive manufacturing companies have begun to delegate the power and responsibility of quality inspection and control to assembly workers on the line. This so-called online (line-stop) repair policy has been receiving increased attention from many manufacturing companies. Through a series of computational experiments, this paper examines the effectiveness of the online repair policy, which empowers workers to assure quality on the assembly line. Under varied assembly line configurations, quality failure costs of the two repair policies are estimated and compared to verify the superiority of the online repair policy. The computational results indicate that the online repair policy can be far more effective in assuring quality and saving costs than the traditional offline repair policy.