Andrew Kusiak

The generalized group technology concept

In this paper two classes of clustering models are considered: (1) matrix, and (2) integer programming. The relationship between the matrix model, the p-median model and the classical group technology concept is discussed. A generalized group technology concept, based on generation for one part of a number of different process plans, is proposed. This new concept improves the quality of process (part) families and machine cells. A corresponding integer programming model is formulated. The models discussed are illustrated with numerical examples.

The facility layout problem

Abstract In this paper, the facility layout problem is surveyed. Various formulations of the facility layout problem and the algorithms for solving this problem are presented. Twelve heuristic algorithms are compared on the basis of their performance with respect to eight test problems commonly used in the literature. Certain issues related to the facility layout problem and some aspects of the machine layout problem in flexible manufacturing systems are also presented.

Intelligent Manufacturing Systems

Introduction - flexible machining and assembly systems components of knowledge-based systems machine learning design of mechanical parts and mechanisms process planning. KBSES - a knowledge-based system for equipment selection group technology - models and algorithms. KBGT - a knowledge-based system for group technology models and algorithms for machine layout. KBML - knowledge-based system for machine layout aggregate scheduling of machining and assembly systems scheduling models and algorithms. KBSS - a knowledge-based system for scheduling in automated manufacturing.

Efficient solving of the group technology problem

Abstract In this paper, two formulations of the group technology problem are considered: the standard formulation and the augmented formulation. The standard formulation is based on the 0–1 machine-incidence matrix and does not consider any costs. In the augmented formulation with each partj, cost c j is associated and the number of machines in each cell is limited to N. This formulation allows the creation of machine cells and part families with a low degree of interaction (or without any interaction, if required) by removing parts with low values of the corresponding costs from the incidence matrix. To solve these formulations, tow very efficient algorithms are presented. The cluster identification algorithm with the computational time complexity 0(2mn) finds optimal machine cells and part families provided that the machine-part incidence matrix has the block diagonal structure embedded. This appears to be the most efficient algorithm developed to date. The cost analysis algorithm is designed to solve the augmented group technology problem. Its computational complexity is 0(2 mn + nlogn). The two algorithms are illustrated in numerical examples.

Data Mining in Manufacturing: A Review

The paper reviews applications of data mining in manufacturing engineering, in particular production processes, operations, fault detection, maintenance, decision support, and product quality improvement. Customer relationship management, information integration aspects, and standardization are also briefly discussed. This review is focused on demonstrating the relevancy of data mining to manufacturing industry, rather than discussing the data mining domain in general. The volume of general data mining literature makes it difficult to gain a precise view of a target area such as manufacturing engineering, which has its own particular needs and requirements for mining applications. This review reveals progressive applications in addition to existing gaps and less considered areas such as manufacturing planning and shop floor control.

Modularity in design of products and systems

Modularity refers to the use of common units to create product variants. This paper aims at the development of models and solution approaches to the modularity problem for mechanical, electrical, and mixed process products (e.g., electromechanical products). To interpret various types of modularity, e.g., component-swapping, component-sharing and bus modularity, a matrix representation of the modularity problem is presented. The decomposition approach is used to determine modules for different products. The representation and solution approaches presented are illustrated with numerous examples. The paper presents a formal approach to modularity allowing for optimal forming of modules even in the situation of insufficient availability of information. The modules determined may be shared across different products.

Grouping of parts and components in flexible manufacturing systems

Abstract In this paper, the problem of grouping of parts and components in flexible manufacturing systems is discussed. The actual grouping is done by modelling the problem as an optimal k -decomposition of weighted networks. Algorithms which are suitable for computer implementation and large problems are developed to find an initial solution and for refining this solution. Bounds on algorithm performance are constructed to give an estimate of the quality of the generated solution. A numerical example illustrates these new techniques.

Machine layout problem in flexible manufacturing systems

This paper analyzes the machine layout problem in flexible manufacturing systems FMSs. We show that the quadratic assignment formulation cannot be used to model the machine layout problem. Four basic types of machine layouts that are frequently encountered in FMSs are presented. A measure to determine the relationship between machines is introduced. Since automated guided vehicles are commonly used to transport material between machines, their motion characteristic is discussed. Two new construction algorithms are presented to solve the machine layout problem in FMSs. They generate solutions with acceptable quality in low computational time. The triangle assignment algorithm TAA is compared to existing methods for 8 test problems and is found to give solutions of better quality than any other construction method published. When compared to existing methods, the computation time performance is attractive.

Short-Term Prediction of Wind Farm Power: A Data Mining Approach

This paper examines time series models for predicting the power of a wind farm at different time scales, i.e., 10-min and hour-long intervals. The time series models are built with data mining algorithms. Five different data mining algorithms have been tested on various wind farm datasets. Two of the five algorithms performed particularly well. The support vector machine regression algorithm provides accurate predictions of wind power and wind speed at 10-min intervals up to 1 h into the future, while the multilayer perceptron algorithm is accurate in predicting power over hour-long intervals up to 4 h ahead. Wind speed can be predicted fairly accurately based on its historical values; however, the power cannot be accurately determined given a power curve model and the predicted wind speed. Test computational results of all time series models and data mining algorithms are discussed. The tests were performed on data generated at a wind farm of 100 turbines. Suggestions for future research are provided.

Efficient models for the facility layout problem

Abstract In this paper, two new models of the facility layout problem are presented: linear continuous with absolute values in the objective function and constraints, and linear mixed integer. The linear mixed integer models have lesser number of integer variables than any other existing formulation for the facility layout problem. While most other linear mixed-integer models available in the literature have been obtained through a linearization of the quadratic assignment problem, the ones presented in this paper are not. The continuous models have an even more compact form. An advantage of the formulations presented in this paper is that the location of sites need not be known a priori. More importantly, two of the formulations model the layout problem with facilities of unequal area. Solving the models presented with an unconstrained optimization algorithm yields good quality suboptimal solutions in a relatively low computation time. The continuous models appear to be more useful for solving the facility layout problem than other models published in the literature.