Joseph Bukchin

Design of flexible assembly line to minimize equipment cost

Abstract In this paper we develop an optimal and a heuristic algorithm for the problem of designing a flexible assembly line when several equipment alternatives are available. The design problem addresses the questions of selecting the equipment and assigning tasks to workstations, when precedence constraints exist among tasks. The objective is to minimize total equipment costs, given a predetermined cycle time (derived from the required production rate). We develop an exact branch and bound algorithm which is capable of solving practical problems of moderate size. The algorithms efficiency is enhanced due to the development of good lower bounds, as well as the use of some dominance rules to reduce the size of the branch and bound tree. We also suggest the use of a branch-and-bound-based heuristic procedure for large problems, and analyze the design and performance of this heuristic.

A weighted approach for assembly line design with station paralleling and equipment selection

This paper studies the problem of assembly line design, focusing on station paralleling and equipment selection. Two problem formulations, minimizing the number of stations, and minimizing the total cost, are discussed. The latter formulation is demonstrated by several examples, for different assembly system conditions: labor intensive or equipment intensive, and with task times that may exceed the required cycle time. It is shown that the problem of assembly system design with parallel stations can be treated as a special case of the problem of equipment selection for an assembly line. A branch and bound optimal algorithm developed for the equipment selection problem is adapted to solve the parallel station problem. Experiments are designed to investigate and demonstrate the influence of system parameters, such as assembly sequence flexibility and cycle time, on the balancing improvement due to station paralleling. An ILP formulation is developed for the combined problem of station paralleling with equipment selection, and an optimal solution of an example problem is presented.

RALB: a heuristic algorithm for design and balancing of robotic assembly lines

Summary This paper describes an heuristic approach for design and balancing of a robotic assembly line. The objective of RALB (Robotic Assembly Line Balancing) algorithm is to balance the assembly line, by allocating equal amount of work to the stations on the line, while assigning the most efficient robot type, out of several different types of robots available for the assembly task, to each workstation, and minimizing the number of workstations and robots used. RALB uses heuristics to limit and guide a Branch and Bound frontier starch, thus leading to solution of very large or difficult problems. A recommendation of the optimal set of heuristic rules is made based on results of extensive testing of RALB with a variety of assembly problems.

Multi-objective design of team oriented assembly systems

This paper presents a design methodology for assembly systems based on teams, where each team is semi-autonomous with well-defined responsibilities. Team oriented assembly systems meet new objectives of modern assembly systems. At the same time, they also create a more satisfactory work environment. The design decisions include the number of teams, the precedence relationship among them, team size, and the work content of each team. The problem solving approach focuses on the structure of the product, and is based on assigning work elements to teams according to the products Bill of Material structure. Five performance measures for the solution quality are introduced. The optimal solution procedure, based on a backtracking Branch and Bound algorithm, is proposed to solve the multi-objective design problem and find an efficiency frontier of all efficient design configurations. Based on the optimal algorithm, a quick and effective heuristic algorithm was developed for solving large-scale problems. The performance of the heuristic is demonstrated through a wide range of experiments. � 2003 Elsevier B.V. All rights reserved.

Lot splitting to minimize average flow-time in a two-machine flow-shop

Lot splitting is a technique for accelerating the flow of work by splitting job lots into sublots, In this paper we investigate the lot splitting scheduling problem in a two-machine flow-shop environment with detached setups and with batch availability. The performance measure considered is the average flow-time which is indicative of the increasingly important manufacturing lead-time. Our contribution is both theoretic and practical for the case of general (not necessarily equal) sublots. We identify properties of the optimal solution and develop a solution procedure to solve the problem. We then present a computational study which indicates that our solution technique is very efficient.

The ergonomic design of workstations using virtual manufacturing and response surface methodology

Abstract The increasing use of computerized tools for virtual manufacturing in workstatin design has two main advantages over traditional methods first it enables the designer to examine a large number of design solutions; and second, simulation of the work task may be performedin order to obtain the values of various performance measures. In this paper a ne~ structural. methodology for the workstation design is presented. Factorial experiments and the response surface methodology are integrated 111 order to reduce the number of examined design solutions and obtain an estimate for the best design configuration With respect to multi-objective requirements.

Team-oriented assembly system design: A new approach

Abstract A new design methodology for team-based assembly systems is presented in this paper. Team-oriented assembly (TOA) systems support the objectives of modern assembly systems, while creating a more satisfactory working environment. Each team is defined as semi-autonomous with well-defined responsibilities. Design parameters are: number of teams, precedence relationship between them, team size, and work content of each team. The problem-solving approach is product oriented and based on assigning Bill of Material (BOM) elements to teams. Performance measures are introduced, and a hierarchical design approach which consists of two stages is presented.

Multi-objective lot splitting for a single product m-machine flowshop line

In this paper, the mean flowtime and the makespan objectives are simultaneously investigated in a single product, m-machine, flowshop system. For this purpose, an efficiency frontier approach is applied and an optimal algorithm for generating all efficient solutions is developed. A comprehensive computational experiment is performed for analyzing the tradeoff between the two objectives and evaluating the proposed algorithm performance. The most-balanced-solution, MinMax, is defined and recommended as a desirable alternative for either the flowtime or the makespan optimal solutions. Results show that when the system is optimized for either the mean flowtime or the makespan, a significant loss in the nonoptimized objective value is observed. On the other hand, adopting the MinMax solution obtains a close to optimal solution in both objectives.

An efficiency frontier approach for the design of cellular manufacturing systems in a lumpy demand environment

Abstract A new multi-objective approach for the cell formation problem in a lumpy demand environment is presented. The objectives addressed in this paper are grouping efficiency and capacity requirements. In lumpy demand the required capacity is affected by demand variability and the correlation between the part types assigned to the cells. We claim that since the required capacity is determined by part types grouping, part type demands variability and their correlation should be taken into consideration as part of the cell formation. This new approach is discussed and formulated as a mixed integer programming model and illustrated by a wide range of typical examples. These examples demonstrate that when using traditional approaches designers do not obtain optimal solutions and may make decisions on the basis of wrong results. The proposed approach helps designers eliminate these problems and produce a reasonable cell design. A genetic algorithm is proposed and examined for designing large-scale systems.

Learning in tele-operations

Abstract Tele-operation is used when a task has to be performed in a hostile, unsafe, inaccessible or remote environment. Examples of tele-operation include the dismantling of bombs by the police and the manipulation of robotic arms in nuclear reactors, in deep seas or in space. Two commonly used methods in tele-operation are direct manipulation and indirect manipulation. In direct manipulation the operator has a direct view of the manipulator and performs mostly mechanical tasks. In indirect manipulation the operator does not have a direct view of the manipulator, and sensors such as closed loop TV systems are used to provide the operator with on-line information. In this case, manipulation requires mental efforts, since the presentation of the manipulator environment is frequently distorted due to the limited ability of sensors to provide a complete and accurate view of reality. In this study a simple pick and place tele-operation task was performed in the direct and indirect modes by the participating subjects. The analysis of the results show that while the very same learning model can be used to analyze the learning process in both modes, the parameters of the models are significantly different. Thus the duration of the learning process, as well as the most appropriate leaching methodology, may differ substantially between the two modes of operation.