Modeling, Analysis, and Improvement of Batch-Discrete Manufacturing Systems: A Systems Approach

Production systems include both discrete part and batch operations, where an individual part is manufactured in a discrete operation, and a group of parts are processed simultaneously, i.e., in a batch, on one machine for a batch operation. Many manufacturing industries, such as battery, aircraft, and automotive, consist of mixed batch and discrete part operations, referred to as batch-discrete lines. Although such operations are widely encountered, analytical studies of these systems are limited in current literature. In this paper, a systems approach is presented to model and analyze batch-discrete lines. First, a Bernoulli machine reliability model for a two-machine batch-discrete system is introduced. Using a virtual buffer to represent the batch processing feature, performance evaluation formulae are derived and system properties are investigated. Using them, improvement analyses and bottleneck identification are presented. Then, the model is extended to systems with a quality inspection device under different control policies. To illustrate the applicability of the model, a case study in a composite part production process is described. Such a work delivers a quantitative tool for production engineers and managers to design, analyze, and improve batch-discrete manufacturing systems.
Note to Practitioners
—Many manufacturing systems in aircraft, automotive, battery, medical device, and defense industries include both batch operation and discrete part processing machines. In a batch operation, multiple parts are manufactured simultaneously on a batch machine, while a single part is made in a discrete part machine. Production lines with mixed batch and discrete part operations are named as batch-discrete systems. Analysis and improvement of such systems are critical to ensure high productivity and quality. However, accurate modeling and analysis of batch-discrete systems are lacking in current literature. To bridge this gap, a novel methodology is presented in this paper. Using a Bernoulli reliability machine model with a virtual buffer concept, performance measures are derived for batch-discrete two-machine lines, as well as the reversed discrete-batch lines. Then system properties, such as monotonicity, interchangeability, and reversibility, are investigated, followed by improvement analysis under constraints and bottleneck analysis. By extending to systems with quality inspections, two quality control policies, to scrap either the current batch or the whole inventory after detecting a degraded part, are studied. In addition, a case study of heating (batch) and trimming (discrete) operations in composite panel production lines is presented, and improvement strategies are investigated, to illustrate how to apply the model and analysis in practice.