Production Process Optimization For OKP Enterprises With Resource-constrained

Nowadays, due to the complexity and variability of the market demand, one-of-a-kind production (OKP) become the mainstream production way. One-of-a-kind production is a costumed production mode. Although such production mode can meet the diverse market needs, there also exists many problems, like long production cycle, frequent production changes, many uncertainty factors(like raw material supply delay, equipment failure, staff absence temporary).Because of these uncertainty factors, the real production process of OKP companies often deviates initial production planning, thus results in delivery delay. How to response to these uncontrollable factors flexibly is an important issue for OKP enterprises surviving and developing in the market with fierce competition.This work pays attention to the uncertainty and variability of OKP enterprises. The production process is optimized to reduce the influence of uncontrollable factors that may occur in the production process, and to prevent the production lag caused by these factors.Firstly, this paper presents the measure criterion of the OKP enterprises production planning adaptive capability to uncontrollable factors. That is production schedule planning robustness. In addition, the concept and measure way of this robustness are clearly defined.In single-order case, resource constrained single-order production process optimization model is proposed. Genetic algorithm is applied to solve this problem. The optimal production schedules with optimized duration time are obtained at first. And then we seek the production schedule with optimal robustness from these schedules. The dual optimization production schedule with optimized duration time and robustness is obtained.In multi-orders case, due to resource capacity constraints, it is impossible to ensure all products can be delivered on time. Goal programming is applied to establish resource constrained multi-order production process optimization model. Genetic algorithm is applied to solve this model. We first pursue optimized delivery delay, and then pursue best robustness. The production schedule with optimized tardiness and robustness is obtained.Finally, the examples are presented to test the validation of the model and algorithm.This paper introduces the concept of the production schedule robustness and builds the optimization model. The optimization of production duration time and robustness is carried on in the production planning development. The results have theoretical significance and practical value for OKP companies arranging production with resource constraints to improve market responsiveness and better adapt to the uncertainty in the production process.