| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5469844 | Procedia CIRP | 2016 | 6 Pages |
The control of todays production systems has become more complex due to an increasing number of products, product variants, randomly incoming orders and non-standardized production processes. Specifically job-shop production is indispensable for single- and small-series- productions with low repetition rates. However, their productivity yields disadvantages compared with flow production. Self-regulating methods of production control like the Decentralized WIP-oriented manufacturing control (DEWIP) by Loedding [2] offer potential for compensating this disadvantages. Though, with an increasing variety in order sequence, it is getting increasingly difficult to estimate the effects of control activities on other orders in the following production flow. Thus, job-shop production with widely ramified material flows is usually organized manually. Decisions to overcome disturbances and deviations from the production plan are made locally by foremen or workers. Those decisions base on their experience and know-how, however with the same deficit regarding the estimation of the subsequent production process concerning disruptions. This paper presents a work in process (WIP) regulating method of production control which has been designed specifically for the requirements of typical job-shop productions. It combines the advantages of load balancing over the complete production, as proposed by Bechtes Load-Oriented Order Release [3] with the adaptivity of decentralized production control, like in DEWIP. By balancing current and prospective utilization via so-called resource accounts, bottlenecks are identified before they appear on the shop floor. Thus, alternative material flows bypassing the bottleneck processes can be activated adaptively as well as measures to extend the capacity can be undertaken. This paper presents the concept and its elaboration to a practical method for job-shop control. In addition, it was implemented in a simulation model in order to demonstrate the suitability and the effectiveness for production control in manual job-shop production systems.
