Improvement of Manufacturing Processes via Process Chain Benchmarking
Particularly innovative products and productivity contribute to the business success of companies in the forming industry. First and foremost, the productivity must be increased in order to resist to the stress of competition – especially rising in low labor cost countries. Investigations have showed that beside the qualification of the operating personnel, the improvement of production facilities and processes can contribute significantly to an increase in productivity. Up to now, small and medium-sized enterprises (SME) have lacked the opportunity to identify their own strength and weaknesses.
The objective of the approach described here is to provide an overview of processes performance in SMEs. For that purpose, the overall manufacturing process chain is analyzed and rated via Process Chain Benchmarking. Attributable to the benchmarking results, each participant can identify the room for improvement for all the sub-processes analyzed and undertake appropriate measures.
A concept based on benchmarking was developed to rate the process chain using key data as well as qualitative features. Checklists are used to describe in detail the overall process chains of the participating enterprises. Based on this data, an optimized reference process model (best practices) is developed by experts. The rating of all sub-processes is based on this reference process chain. Each sub-process is rated between 1 and 10, which expresses the deviation from the best-practice. 10 points mean no deviation from the reference, whereas 1 point shows complete deviation from the reference. This rating can provide an informative basis for the performance of each company compared to another. To deduce ascertained measures that improve specific sub-processes, cost-benefit-estimations must be made by the respective enterprise.
Process Chain Benchmarking has been employed successfully in stamping shops as well as roll forming enterprises. Due to an expansion of the benchmarking pool, the approach will be developed further. A set of key data will be elaborated to replace the qualitative rating of the process chain. This will help to eliminate subjective influences on the rating of sub-processes.