Bobbie L. Foote

Inspection errors and statistical quality control: A survey

Abstract The presence of inspection or measurement errors may seriously affect the level of protection afforded by a statistical quality control procedure. In order to adequately compensate for such errors, the quality control analyst must be able to model their occurrence and incorporate them into the design of the procedure. This paper surveys the current state of knowledge in this area, points out the shortcomings of the present approaches and suggests future lines of investigation.

Spectral analysis in quality control: a control chart based on the periodogram

Variations in manufacturing processes are expected to fluctuate around a constant level called the process mean. This article is concerned with the development of a control chart that detects cycles in the process mean. The new control chart, the spectral control chart, is based on the periodogram. The value plotted at each point in time is the ratio of the largest periodogram ordinate to the average of all ordinates. When an observation falls above the prescribed control limit, an out-of-control signal is given. The spectral control chart is compared with the Shewhart and geometric moving average charts. Data obtained from Monte Carlo simulations show that the spectral control chart is superior for detecting cyclic variations but that it is not effective for detecting shifts in the process mean. Thus the spectral control chart should be used along with existing control charts so that both shifts and cycles in the process mean can be detected.

On the implementation of a control-based forecasting system for aircraft spare parts procurement

The implementation of a new control-based forecasting system (SDF) in 1989–1991 at the Aviation Supply Office, Philadelphia, Pennsylvania, is documented. The philosophy, experience, principles and formulas are presented with results from three implementations.

Hybrid genetic algorithm for container packing in three dimensions

The concept of genetics using multiple-chromosomes is applied to a 3D container packing problem. The 3D packing problem deals with packing a given set of regular shaped boxes of different sizes and weights into larger containers. The algorithm must seek to minimize the wasted space under a constraint: the heavier and the larger boxes must be placed below the lighter ones. The present emphasis is to find a good solution quickly by heuristic means. A set of heuristic rules is incorporated into the genetic algorithm (GA) approach to aid in optimization. This hybrid GA yields an optimization algorithm that outperforms either of the parts. The simulation results showed that the new algorithm has better adaptivity for large problems and near optimal solutions for small problems.<<ETX>>

An optimal load flow study by the generalized reduced gradient approach

Abstract A new operations research model of optimal load flow solved by nonlinear programming methods (the generalized reduced gradient algorithm) is presented. As compared to existing optimal power flow models, this model incorporates network performance variables such as scheduled bus voltages as well as topological and elemental constraints. In addition, the development, sensitivity, optimality and efficiency of the model are explored. Several example problems are implemented and solved. Detailed discussions about the ability of the model to work under a wide variety of network contingencies such as loss of generation or load, loss of a line, and network faults are presented. The model is also briefly examined for its use in the study of network voltage regulation.

Computational feasibility of multi-criteria models of production, planning and scheduling

Abstract This paper surveys the applications of multi-criteria decision making (MCDM) methods to production planning, scheduling, and sequencing problems. The basic structure of the decision models are described by their objectives and the resulting models are classified by decision variables into the areas of Aggregate Production Planning, Disaggregate Production Planning, Production Scheduling, and Single Machine Sequencing. The problem sizes that have been solved are summarized to determine how practical it is to use MCDM.

Automatic computation and drawing of facility layouts with logical aisle structures

A fast heuristic for the facilities layout problem including aisle location is developed. The procedure utilizes the scatter diagram of Drezner to obtain a relative location between departments. A simple modification of the new algorithm produces a powerful technique for pure and near-pure flowshops.

The Effect of Inspector Accuracy on the Type I and Type II Errors of Common Sampling Techniques

The single sample and sequential sampling models are presented in a form which includes inspector error. The effect of inspector errors on the probability of type I and type II errors is discussed...

Assignment problems in single-row and double-row machine layouts during slow and peak periods

Abstract Given the plant layout, the number of workers, the maximum number of machines that a worker can handle, and the preferences between each worker and each machine, the problem to minimize the deviations of workloads assigned to workers and to maximize the total preference between each worker and each machine is considered in the semiconductor industry. The number of workers is fixed (no part time workers) because of the high expense of technology education and the increase of current employees. Since the workforce assignment problem in this article is in NP class, several heuristic algorithms are presented according to two types of plant layouts during two types (slow and peak) of periods. The proposed algorithms are developed based on the combination of a mixed model scheduling, simulated annealing technique and graph theory. The solution generated satisfies the zone constraint (machines assigned to a worker are adjacently located). Computational results show that the presented algorithms can find a good solution quickly.

Production planning & scheduling: Computational feasibility of multi-criteria models of production, planning and scheduling

Abstract This paper surveys the applications of multi-criteria decision making (MCDM) methods to production planning, scheduling, and sequencing problems. The basic structure of the decision models are described by their objectives and the resulting models are classified by decision variables into the areas of Aggregate Production Planning, Disaggregate Production Planning, Production Scheduling, and Single Machine Sequencing. The problem sizes that have been solved are summarized to determine how practical it is to use MCDM.