Pedro M. Vilarinho

A two-stage heuristic method for balancing mixed-model assembly lines with parallel workstations

This work presents a new mathematical programming model for the mixed-model assembly line balancing problem with parallel workstations and zoning constraints. It allows the user to control the process to create parallel workstations. The models primary goal is to minimize the number of workstations along the line, for a given cycle time, and its secondary goal is to balance the workloads between and within workstations. A two-stage procedure, using a simulated annealing approach, was developed to tackle this complex problem. The first stage of the procedure looks for a sub-optimal solution to the problems primary goal, whilst the second stage deals with the secondary goal. The procedure is illustrated with a numerical example and the results from computational experiments show that even for large-scale problems the proposed procedure performs very well.

A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II

Mixed-model assembly lines allow for the simultaneous assembly of a set of similar models of a product, which may be launched in the assembly line in any order and mix. As current markets are characterized by a growing trend for higher product variability, mixed-model assembly lines are preferred over the traditional single-model assembly lines. This paper presents a mathematical programming model and an iterative genetic algorithm-based procedure for the mixed-model assembly line balancing problem (MALBP) with parallel workstations, in which the goal is to maximise the production rate of the line for a pre-determined number of operators. The addressed problem accounts for some relevant issues that reflect the operating conditions of real-world assembly lines, like zoning constraints and workload balancing and also allows the decision maker to control the generation of parallel workstations.

A simulated annealing approach for manufacturing cell formation with multiple identical machines

Abstract One of the crucial steps in the design of a cellular manufacturing system is the cell formation problem, which involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. When modelling this problem it is usually assumed that the specific machine in which each operation is carried out is known. In a cellular manufacturing system where multiple, functionally identical, machines are available, a new degree of freedom can be introduced into this problem––the allocation of the operations to specific machines. In this paper a mathematical programming model for the cell formation problem with multiple identical machines, which minimises the intercellular flow, is presented. Due to the combinatorial nature of this problem a simulated annealing algorithm was developed to solve it.

ANTBAL: an ant colony optimization algorithm for balancing mixed-model assembly lines with parallel workstations

This paper presents ANTBAL, an ant colony optimization algorithm for balancing mixed-model assembly lines. The proposed algorithm accounts for zoning constraints and parallel workstations and aims to minimize the number of operators in the assembly line for a given cycle time. In addition to this goal, ANTBAL looks for solutions that smooth the workload among workstations, which is an important aspect to account for in balancing mixed-model assembly lines. Computational experience shows the superior performance of the proposed algorithm.

Combining heuristic procedures and simulation models for balancing a PC camera assembly line

In this paper, a mixed-model PC camera assembly line balancing case study is presented. The aim of the study is to establish different line configurations, for varying levels of demand. In the first stage of the study, a heuristic procedure previously developed by some of the authors, based on the simulated annealing meta-heuristic, is used to derive line configurations with a minimum number of workstations and a smooth workload balance between and within the workstations. In the second stage, the solutions provided by the heuristic are used as an input to discrete event simulation models in which certain manufacturing parameters that analytical procedures have difficulty to accommodate, namely, stochastic times, machine breakdowns, rework, etc. are introduced. These simulation models derive different performance measures (e.g. flow times and resources utilization) that provide operational support and help fine-tune the line configurations. This paper reports on the collaborative study between the Department of Economics, Management and Industrial Engineering of University of Aveiro and a major manufacturer of electronic consumer goods.

Meeting demand variation using flexible U-shaped assembly lines

Nowadays, companies must be able to provide a higher degree of product customisation to fulfil the needs of the increasingly sophisticated customer demand. This can only be achieved by having flexible production systems, able to cope with extended product ranges and with the uncertainty and variability of demand in the current market environment. The purpose of this paper is to present a contribution related to facilities design that accounts for this issue, by presenting flexible U-shaped line configurations for an assembly system. In this type of line, whenever the production volume or product mix changes, the only modification in the line will be the number of operators working in the line, as the physical workstations remain fixed. The relevance of the problem is stated and a heuristic procedure, based on ant colony algorithms, developed to address this problem is described. The results of the application of the proposed procedure to an assembly line of a major manufacturer of electronic security systems are reported.

Using simulation for manufacturing process reengineering: a practical case study

This paper presents a simulation study carried out to solve a problem of manufacturing process reengineering. The specific company in which the study took place is a medium size manufacturer of chest freezers, which required an in-depth analysis of its manufacturing operations in an attempt to increase its throughput and overall productivity. A simulation model of the current manufacturing system was developed to ascertain its limitations and problems. The relevant operational performance measures were analyzed in order to allow for the proposal of a set of changes to the actual manufacturing operations. In order to support the decision process concerned with the implementation of the suggested changes, these were included in the simulation model. The outcome of the simulation study was taken into account by the decision-makers and the recommendations are being implemented.

Lot Sizing and Scheduling in Parallel Uniform Machines – A Case Study

This chapter presents the problem of scheduling tasks in uniform parallel machines with sequence-dependent setup times. The problem under analysis has a particular set of constraints, including equipment capacity, precedence tasks, lot sizing and task delivery plan. This kind of problem should be considered an operational planning problem and is found in different types of industries, namely, in the textile industry.