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Schedules for a two-stage hybrid flowshop with parallel machines at the second stage

Approximate solution algorithms are developed to find a minimum makespan schedule in a two-stage hybrid flowshop when the second stage consists of multiple identical machines. Computational experience comparing the ‘approximate’ makespans with their respective global lower bounds for large problems indicates that proposed polynomially bounded approximate algorithms are quite effective. It is shown that the proposed heuristic algorithms can be used to improve the efficiency of an existing branch and bound algorithm.

Scheduling a two-stage hybrid flowshop with separable setup and removal times

Abstract This paper considers the two-stage flowshop scheduling problem where each stage consists of several identical parallel machines and the setup and removal times of each job at each stage are separated from the processing times. A polynomial optimization algorithm is developed for the special case where the first stage contains only one machine and the number of identical parallel machines at the second stage is equal to or greater than the total number of jobs. In view of the NP-completeness of this problem, four heuristic algorithms are developed for the case where there is one machine at stage 1 and the number of identical parallel machines at the second stage is less than the total number of jobs. The proposed heuristic algorithms are empirically tested to determine their effectiveness in finding an optimal schedule.

Is Time a Competitive Weapon among Manufacturing Firms

Considers the recent development of time‐based management as a way of enhancing the competitive position of a manufacturing organization. Based on a review of literature related to time‐based management, several possible relationships between the use of time‐based competition and its benefits in attaining stated business goals are defined. Results of empirical investigation using the manufacturing firms in the State of Indiana are discussed and some preliminary conclusions about the use of time‐based competition strategies among manufacturing organizations are drawn. The results of this study suggest that a full‐scale study of international scope will be beneficial to judge the use of time as a competitive weapon among manufacturing firms.

A comparative study of US manufacturing firms at various stages of just-in-time implementation

This study explores whether there are differences among the companies at various stages of just-in-time (JIT) implementation based on factors which were considered relevant in the literature. The factors are categorized as internal and external. Internal factors relate to questions involving product, equipment and process, work-force and top management commitment. External factors deal with supplier and customer issues. Responding firms were categorized into five groups based on their status of JIT implementation, ranging from totally non-JIT to partial and full implementation. The findings of this study suggest that some of the issues such as supplier proximity and the lead-time of the supplier, which have been traditionally considered to be important, are not major impediments to JIT implementation. However, there are some issues such as top management commitment which may facilitate or inhibit the move toward JIT implementation.

Selecting Scheduling Heuristics Using Neural Networks

This paper discusses the application of neural networks to select the best heuristic algorithm to solve a given scheduling problem. The two-stage hybrid flowshop with multiple identical parallel machines at the second stage is used as an example to discuss the process of selecting a scheduling heuristic through a neural-network approach. This paper uses the genetic-algorithm-based approach for training the neural network and shows that the suggested neural-network approach is quite effective and efficient for selecting the best heuristic algorithm for solving a given scheduling problem.

Tour scheduling with dynamic service rates

This paper examines the benefit of incorporating a group of employees that exhibit dynamic service rates into scheduling tours in a service operation. The service operation that is examined includes a fully productive core (full‐time) workforce along with a contingent (full‐ and part‐time) workforce that experiences the learning effect. Two methods that account for the learning effect are analyzed along with two methods that do not consider learning effects. The schedules generated by each method are tested in a simulation of the service environment. The results of a full‐factorial experiment indicate that methods that account for learning effects will yield superior solutions over a variety of operating conditions when compared to alternative methods that do not consider learning effects. The performance improvement of schedules generated with the most precise learning curve method was substantially and significantly better than the other methods. The conditions in which the learning curve methods provide the most benefit are explored.

Managing Homo Sapiens

The evolutionary process in general, and human evolution in particular, are basic to comprehending Homo sapiens. Human evolutionary heritage predisposes human behaviour, and that is what all management systems (including Total Quality Management) seek to affect via training, coordination, and motivation. The evidence of behavioural biology and evolutionary psychology points to two human traits that bear importantly upon the success of managerial efforts. One is the desire for distinction or social status. A comprehension of this behavioural tendency allows managers to anticipate and coordinate employees risk-taking activities. A second prominent characteristic is the tendency to reciprocate altruism. Understanding reciprocal altruism and the trade-offs between it and status seeking assists mangers in knowing when it is productive to form work teams, and how to control and motivate teams. The evolutionary perspective we present offers insights into difficulties that frequently arise when Total Quality Management systems are implemented.

A multistage approach for production and workforce planning in long-cycle product environments

Abstract Aggregate production planning (APP) has been studied extensively for the past two decades. The APP problem, also called production and workforce scheduling, is to determine the optimal workforce and production level in each period of the planning horizon in order to satisfy demand forecasts for these periods. The advantages of the APP are low cost of data collection and computational cost of the running model; the accuracy of data; and, effective managerial understanding of the results. If the product of concern takes longer than one period, it is called a long-cycle product. Examples of long-cycle products are aircraft, ships, buildings and special machines. A detailed model incorporating dynamic productivity and long-cycle products considerations is presented to solve the problem of production and workforce planning. Using a multistage production system approach, a search technique is developed to solve this class of problems where the objective function is linear and some of the constraint coe...

Production and work force planning in manufacturing systems for long-cycle products: A survey

Abstract The production and work force scheduling problem for long-cycle products is one of determining the optimal production and work force levels throughout the planning horizon for products requiring many months of effort prior to completion. If the product can be finished in the same period in which it is started, it is called a short-cycle product. Most repetitive manufacturing companies deal with short-cycle products. On the other hand, if it takes longer than one period to complete a product, it is called a long-cycle product. Examples of long-cycle products are aircraft, ships, buildings, and special machines. This paper presents a review of the studies on production planning for long-cycle products and points out the need for research incorporating the learning effect in this area.

Issues and challenges of cross-functional integration: introducing ERP in MBA courses

An increasing number of universities have entered or are contemplating entering into alliances with leading vendors of ERP software and are redesigning both undergraduate and graduate curricula to help students understand the requirements and the design of enterprise-wide systems solutions through the use of an ERP system. Ball State University joined the SAP alliance program in spring 2002 and has been offering ERP courses both at graduate (MBA) and undergraduate levels since then. Different approaches have been used by various schools to introduce SAP to the curriculum. Ball State Universitys approach is to deliver a set of modules by a team of faculty from six different departments. This paper articulates our approach for teaching ERP courses to understand cross-functional integration at the MBA level. The paper also highlights various technology, pedagogical and human resource issues and challenges.