The selection of an optimal PPC configuration is a difficult task which depends on several factors and needs to be taken more and more frequently, especially in the rapidly changing economic environment. An interesting approach for the selection of the right PPC strategy can be found in the information/control/buffer (I/C/B) portfolio by Schwarz . This framework analyzes different PPC strategies in the dimensions information system, control system, and buffer system. According to Schwarz , an operation must select the PPC strategy based on the total costs of these three components. His framework provides an elegant solution for the PPC configuration problem by combining the different dimensions on the common measure costs. However, the evaluation study showed that the I/C/B portfolio needs to be updated in some of the dimensions to fulfill present needs. The main drawback of the I/C/B framework is the missing consideration of the requisite flexibility of the manufacturing system based on the customer requirements. The simulations showed that the product flexibility has a major impact on the performance of a PPC system. Furthermore, the evaluation study showed a relationship between data availability and PPC model accuracy. Based on that, the I/C/B decision framework was adapted and extended (see Fig. 4).
The new framework presented in Fig. 4 is grounded on three basic systems: the production system, the information system, and the PPC system. Furthermore, indirect factors that cover e.g. knowledge impacts are introduced additionally. The system performance results out of the design and the interactions between these factors.
The production system is mainly characterized by its supply variability and the requisite flexibility. The supply variability includes effects originating from set-up activities, breakdowns, and quality defects. The requisite flexibility originates from the customer requirements in terms of product variations and delivery time expectations. The evaluation study shows that the aforementioned factors have a major impact on the overall performance of all PPC approaches. Despite the best practices in PPC configuration, standard measures using lean tools and complexity management approaches have to be taken to gain control over these highly influencing factors. The joint configuration of the information system and the PPC system is the major challenge in the selection process. Due to the interaction between the information system and the PPC system that was shown in the evaluation study, an approach different to the I/C/B portfolio was followed (joint consideration of the two systems). The quality and availability of external (customer) and internal (supply) data have remarkable influences on the selection of a fitting PPC model. Next to the direct factors of the production, information and PPC system, indirect factors also have an influence on the systems performance. These indirect factors can be mainly attributed to the required skill and knowledge level for the different PPC methods. Especially pull-type PPC systems require a certain discipline and responsibility on the shop floor to operate properly. Overall it can be said that these factors result in a performance of the system with a certain use of the different buffering systems (inventory, capacity, and time) to match the demand. As the evaluation study showed, simulation is a key technique to reveal the performance. The decision on the optimal PPC configuration should be based on the overall system costs for the information system, the PPC system, the resulting system performance and the costs for the indirect factors .
As a consequence of the previously described facts and circumstances, simple planning methods could surprisingly return a solution at the overall cost optimum when inventory keeping is cheap. That does not necessarily mean that an investment in PPC systems using in-detail models and high quality data are not worth the effort – amongst others it strongly depends on the cost factors. To conclude, this generally means that an enterprise has to first calculate the potential benefits and the return of an investment in the informatization of the production and then set up an aligned and cost optimal configuration for its operations.