| Summary: | 碩士 === 淡江大學 === 管理科學研究所碩士班 === 94 === Among affiliated researches about manufacturer’s selling and producing at the same time, most inventory models run on the premise that production process is in the normal situation, meaning that all factors which might influence product process are totally avoided, and the products are of no defect. However, machine might deteriorate after being used for a long while, what’s more, employee might operate machine in the wrong way, the two possible factors mentioned above might cause production process out of control, producing defective products. As a result, many researchers have built the inventory model on the basis of the imperfect production process.
However, most references about imperfect production process simply focus on how to reduce defective products and maintain production equipment, but when it comes to the products backlogging, they often assumed that which is not allowed to happen. In real situation,when backlogging happens, some customers are willing to wait until replenishment because they are loyal to this brand or company, while others are not. Furthermore, in some cases that some customers who are willing to wait until replenishment originally ,but if they wait too long, while they will more impatient and go elsewhere, may buy the goods from the competitors. As a result, the inventory model with regular backlogging rate, or the willingness of a customer to wait for backlogging during a shortage period declines with the length of the waiting time, involved might be more persuasive and worth treating.
What’s more, enterprises lay high emphasis on improving production process quality nowadays. In order to attain higher production quality level, they invest more in production process quality improvement with the purpose of reducing product defective rate.
In conclusion, this thesis develop three inventory models under the situation that the production process is imperfect. In chapter two, it builds the inventory model allowing partial backlogging rate, assuming which is a constant. In chapter three, the factors related to backlogging rate and customers’waiting time for the next replenishment are involved in the inventory model. In chapter four, it treats how to improve the production process quality by investing, considering partial backlogging rate, which correlates with customers’ waiting time for the next replenishment. The goal of building these inventory models mentioned above are to derive minimum total cost, and among them, the producing time and product quality level are common decision variables. At last, for all models proposed in this thesis, it uses numerical examples and sensitivity analysis to illustrate the effects of the change of the different parameters on optimum solution.
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