Manufacturing Model Extension--论文代写范文

在产品开发原型建立后,关于产品的各个方面的问题，数据的收集也很重要。在汽车行业中,这些是潜在的问题。由于产品的复杂性,产品发展不能进步,产品开发时间的决定并产生重大影响。下面的paper代写范文进行论述。

Abstract
  Thus far, the net revenue model has the capability of evaluating the performance of manufacturing facility during manufacturing launch. It considers neither impact of product development nor customer reaction to product quality on net revenue and on the optimal manufacturing launch path. This section will discuss the extensions needed for the model to make that connection.The first step towards extending the model is to identify the specific parameters within the net revenue model which should be impacted by product development and customer reaction to quality. The feature that is common to all of these activities is the issues/defects. Defects impact the manufacturing launch path through their impact on rework, rejects and downtimes and in turn through the costs that are affected by these variables. Defects also impact product quality and consequently customer reactions, which in turn impact willingness to pay, vehicle price and thus firm revenues. Finally, the number of issues, and therefore the number of issues are a function of the product development strategy. While the concept of linking these phases of a vehicle project life by tracking the impact of issues/defects is clear, representing the details of the interactive effects can be complicated.

 Latent Issues 
  During product development after the prototype is built, the data on number of problems regarding various aspects of products are collected. In automotive industries, these are called latent issues, usually with the units of issues per thousand vehicles (IPTV). The number comes from a multitude of tests done on a few vehicles, which is then extrapolated to IPTV number. As product development progresses, this number gradually decreases, representing the improvement in the product design. Although one would like to believe that this number would reduce to zero before the product design is transferred to be manufactured in a facility, this is not realistic in any complex product with a combinatorial number of potential failure modes. Due to the complexity of the product and the number of components in the final product, product development cannot progress until the product is completely issue-free. However, the product development duration decision does have a significant impact on the number of issues entering the manufacturing process as well as the final product quality. Thus, the issue is determining when to stop finding and solving problems.

  Due to variations in product manufacturing, latent issues may exist in some products and not in others of the same product design. The issues that exist in a product are defects. Once in the manufacturing facility, defects can manifest themselves as manufacturing events. The higher the number of latent issues, the higher the probability of manufacturing events. Defects that caused manufacturing events are eliminated. However, while the defect itself is also remedied, only sometimes are the underlying causes discovered and fixed. Only after the root cause of a defect is solved will the defect be permanently eliminated from all subsequent products.

  The defects eliminated are specific only to the one product that causes manufacturing event, which means the same defect in other products can still cause an event. However, there is a probability that the workers or supervisors investigate the problem, understand the root cause, and make changes to the original product design so that the defect is permanently eliminated from all subsequent products. Indeed, subject to resource constraints, this is common practice during product launches.

  The number of defects in the finished product is an indicator of product quality, which directly influences reputation of the firm and therefore the demand for the product. The product quality will also determine the number of product failure and therefore the warranty cost incurred to the firm. On the cost side, warranty is the cost incurred to the manufacturing firm when the purchased products fail, needing repairs or part replacements. The number of product failures, or faults, of a product manufactured in period i over the warranty period is directly proportional to the number of defects in finished product and failure rate function.

 Effect of Uncertainty on Product Launch Decisions
  While Chapter 5 explores the sensitivity of product launch decisions to various endogenous and exogenous factors, the model has yet to fully incorporate uncertainty into calculating product 98 launch decision performance. It would be beneficial to understand not only how the average value of a factor, but more generally how its distribution affects the performance of a decision. Some of the factors that can be affected by uncertainties are selling price, demand, product failure rate, and initial reputation. For example, the firm cannot be fully certain at the beginning of the manufacturing launch what the competitors and overall economy will do, and therefore cannot know the price, and consequently, the demand the product will obtain. The uncertainty in selling price stems from the many uncertainties in the market: level of competition, imperfect information, and customer demand. 

  The firm has no way of exactly measuring how much the customer knows about its products, the accuracy of that information, or how its product compares to other firms’ products. Even with that, each customer values different features of a product differently. For example, one customer might value a computer with good graphics capability, while another might value a computer with good audio output and all of these might change because of various uncontrollable factors. Therefore, it is difficult for the firm to expect how the products would perform once it is released in the market, both in short term and throughout its lifecycle. Uncertainty of firm reputation can affect the product launch decision performance. 

  As shown in Figure 4-7, the effect of reputation on the product price is asymmetric; an increase in price from increased reputation is not equal to the decrease in price from decreased reputation of the same degree. In fact, the magnitude of increase is about half of the magnitude of decrease, for the same change in reputation. Consequently, firms should be even more careful about any neg impact on reputation, as there is more to lose than to gain with reputation uncertainty. ative Monte Carlo simulation can help facilitate such analyses. By randomly generating inputs based on specified probability distribution functions, the model can take the inputs and generate the net revenues based on fixed product development duration and ramp-up. The net revenues can then averaged and that is the expected net revenue for that product development duration. The optimal product launch decision is the one that results in the highest expected net revenue. Furthermore, the robustness of product development duration and cycle time ramp-up can also be investigated by studying the resulting distributions of costs and revenues, or even the elements of cost such as material cost, labor cost, or warranty cost. (paper代写)

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