Complexity has been identified as a ubiquitous and ever increasing property of manufacturing systems. Conventional theories of management lack the tools to describe, analyzse, and manage complexity, and can, in turn, no longer cope with the issues it gives rise to. New approaches are offered by complexity science, namely by computational mechanics. In the paper, a method for complexity assessment is proposed and illustrated on real industrial data. The results of the presented case study suggest a distinct relationship between complexity and throughput, and indicate that the tool used has a major impact on complexity.
COBISS.SI-ID: 11870235
The aim of this paper is to contribute to complex systems thinking in manufacturing organisations through the development of a metric for operational complexity. Operational complexity is concerned with the temporal aspects of coordination and control in manufacturing systems. Statistical complexity from computational mechanics theory is proposed as the metric. The metric can potentially be used to support decision making by objective assessment of complexity. The properties of the metric are explored through simulation studies. The simulation results confirm that the proposed metric captures the intuitive notion of complexity. It is shown that operational complexity is influenced by internal factors such as system structure, as well as external ones such as demand, and that complexity can be managed through the application of appropriate control methods. A case study is presented that applies the metric to real production data. The case study shows that the global recession had resulted in a decreased operational complexity of outputs.
COBISS.SI-ID: 11924251
Qualitz control in production of the power transmission belts currently relies mostly on visual inspection by skilled workers. They primary inspect belt geometry for defects like small bumps, dents and unformed teeth. Despite the controller experience, the result depends on the persons mood and general condition. To avoid subjective inspection, an experimental system for automated inspection of the belt geometry is developed. It operates on the basis of the laser triangulation system, capable of acquiring a cloud of points in 3D space representing a complete belt surface. By processing the acquired data cloud, most typical belt defects can be identified and assessed. We demonstrate two different methods of data processing. The first one imitates the established manual procedure, where the individual tooth profile is compared to a template specified by a technical documentation. The second method uses a novel approach based on the deviation map. That enables automated analyses of the complete tooth surface (not only profile), identification of 4 typical surface defects and their pass/fail quality assessment. We found shape of the surface defects sufficiently recogniyable in the acquired data cloud, which means that point measurement accuracy of the developed laser triangulation system is sufficient. We demonstrate identification of the typical surface defects. We found that further work is needed to develop pass/fail criteria of the quality assessment to comply with the requirements of the industry.
COBISS.SI-ID: 11800091