Industral Engineer, Iran University of science and technology
Production and non-productive equipment and personnel delays are a critical element of any production system. The frequency and length of delays impact heavily on the production and economic efficiency of these systems. Machining processes in wood industry are particularly vulnerable to productive and non-productive delays. Whereas, traditional manufacturing industries usually operate on homogeneous raw material, in a restricted environment with closely controlled processing guidelines. The logging industry must continually deal with a raw material that comes in many different shapes, sizes and performs in an environment that is different from site to site. Furthermore, loggers; rarely have the opportunity to follow a predetermined production sequence, as men and machines must maneuver as conditions dictate. As a result machining systems can experience a broad range of delays that vary widely in frequency and length. The purpose of this study was to apply Markov process models to the analysis of delay times in machining processes. Such an approach will permit the random components of machining process to be integrated into a flexible mathematical model, using theoretical probability distributions, and providing analytic solutions to proportions of productive delay time.