Integrative Approach to Online Quality Management: Process Control and Packout Verification in an Intelligent Manufacturing Workcell.

The current global competition and the economic situation in the United States and the world is forcing industries to produce quality products quickly and at a competitive price. Many industries are aiming towards world class manufacturing objectives like responsive delivery, defect free product and declining cost. Industries in the present environment can survive and produce the quality products to customer expectations only if they implement new technologies. The key element in the success of industries is using the continuous process improvement strategies like reducing process variability and reducing response time to process deviations. Achieving quality in manufacturing processes is an important part of the job description of everyone concerned with the manufacturing operation. The greatest savings can come when a quality system can immediately inform appropriate personnel when process problems occur, and can then assist in ensuring rapid response at the lowest possible level in the organization. This type of system adds not only to the bottom lux but also to the job satisfaction of all concerned [John, 1992]. The quality tools of the future are those that operate under a different scenario: the computer systems that collect the data also automatically do the analysis, interpretation, detection and correction, along with exception-based alarming and reporting. In this research, we examine the potential benefits of an integrative approach to on-line quality management. The motivation for this research comes from a field study with a printed circuit board assembly and instrumentation cluster manufacturer. The company made substantial investments in setting up elaborate systems for on-line data collection and monitoring of process status. While these modern quality control systems provided a rich database, their application in quality management was rather limited. This is partially due to the lack of appropriate methodology for quality decisions. The objective of this research is to develop an integrative approach to process control and packout verification of products. When the developed approach was implemented, it enabled the company to reduce their Problem Resolution Requests (PRRs) by 25% and was a cost avoidance of approximately $600,000 annually

On Discrete-Event Simulation and Integration in the Manufacturing System Development Process

DES is seldom used in the manufacturing system development process, instead it is usually used to cure problems in existent systems. This has the effect that the simulation study alone is considered being the cost driver for the analysis of the manufacturing system. It is argued that this is not a entirely correct view since the analysis has to be performed anyway, and the cost directly related to the simulation study is mainly in the model realization phase. It is concluded that it is preferred if the simulation study life cycle coincides with the corresponding manufacturing system's life cycle to increase the usability of the simulation model and to increase efficiency in the simulation study process. A model is supplied to be used for management and engineering process improvements and for improvements of the organizational issues to support simulation activities. By institutionalizing and utilizing well defined processes the conceived complexity related to DES is considered to be reduced over time. Cost is highly correlated to the time consumed in a simulation study. The presented methodology tries to reduce time consumption and lead-time in the simulation study by: (i)~reducing redundant work, (ii)~reducing rework, and (iii)~moving labor intensive activities forward in time. To reduce the time to collect and analyze input data a framework is provided that aims at delivering high granularity input data without dependencies. The input data collection framework is designed to provide data for operation and analysis of the manufacturing system in several domains. To reduce the model realization time two approaches are presented. The first approach supplies a set of modules that enables parameterized models of automated subassembly systems. The second approach builds and runs the simulation model based on a copy of an MRP database, i.e. there is no manual intervention required to build the simulation model. The approach is designed to forecast the performance of an entire enterprise. Since the model is generated from a database, the approach is highly scalable. Furthermore, the maintenance of the simulation model is reduced considerably