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Globally, industries and economies have undergone rapid development and expansion over the last several decades. As a result, global warming and environmental contaminations have resulted in climate change and jeopardized food security. In many developing countries, already decreasing crop yields are threatened by extreme weather and soil damaged by genetically modified food, making environmental problems worse and increasing food and organic product prices. For these reasons, this study proposes a hybrid multicriteria decision-making (MCDM) model for new product development (NPD) in the light-emitting diode- (LED-) based lighting plant factory. First, literature reviews and expert interviews are employed in constructing a list of decision-making objectives and criteria for new product development. Then, a fuzzy Delphi method (FDM) is used to screen the elements of the objectives and criteria, while a fuzzy decision-making trial and evaluation laboratory (FDEMATEL) is used to determine the relationships among the objectives and criteria. Finally, a fuzzy analytic network process (FANP) and a composite priority vector (CPV) are manipulated to determine the relative importance weights of the critical objectives and criteria. Results show that the proposed method can create a useful and assessable MCDM model for decision-making applications in new product development, and a case study is herein performed to validate the feasibility of the proposed model in a Taiwanese LED-based lighting plant factory, which not only provides the decision-makers with a feasible hierarchical data structure for decision-making guidance but also increases the competitive advantages of trade-offs on developing novel products.

This study would create a decision making model for new product development (NPD) in light-emitting diode (LED) plant lighting industry. At first literature reviews and expert interviews will be employed to list five perspectives and 19 criteria thereof. A fuzzy Delphi method (FDM) will be then used to screen factors for the criteria. An interpretive structural model (ISM) will be managed to get the relationships among the perspectives and among the criteria. A fuzzy analytic network process (FANP) will be finally manipulated to compute the weights of all criteria. Results of the study will provide an assessment model of NPD decision making for LED plant lighting industry.

In the current thin-film transistor liquid crystal display industry, the light guide plate (LGP) of the backlight module has become thinner and smaller, and the backlight module needs to be illuminated uniformly and effectively. The parameter setting for the photolithography process of a LGP stamper often relies on the engineers’ experiences by means of trial-and-error or design of experiment to obtain a suitable and more reliable process parameter setting, which requires a large amount of time, manpower, and cost. This research proposes a novel two-stage optimization system for photolithography process integrating the Taguchi method, back-propagation neural networks, genetic algorithms, particle swarm optimization, and related technologies to effectively generate optimal process parameter settings. The first stage is to reduce the process variance. The second stage is to find the final optimal process parameter settings for the best quality specification. Experimental results show that the proposed system can create the best process parameters which not only meet the quality specification for the micro-dots on the photoresist, but also effectively enhance the overall process stability.

Due to the increasing advancement in technology and limited resources as well as environment being polluted at the same time, the natural solar energy, which has the advantage of environmental protection and being the newly developed approach, will become the rushing field of study around the world in order to implement energy efficiency and reduce carbon pollution. In the meantime, the solar industry technology and new product development have become the considerations to the survival and competitiveness of enterprises. In this study, literature review and expert interviews are utilized to obtain five major key dimensions and 19 subordinate criteria regarding new product development. The Interpretive Structural Model (ISM) is employed to obtain the dimension-dimension and criterion-criterion dependence relationship, and used the Fuzzy Analytic Network Process (Fuzzy ANP) to determine the top priority weight for assessment improvement in the new product development solutions of the enterprises.

In a highly competitive economic society, in order to survive and maintain competitiveness, enterprises must constantly seek beneficial investment opportunities to keep a leading position in competition. The development of new products is the most difficult task in such a process. With solar module industry as the theme, this study explored the new product development decision-making issue and summarized five major key dimensions and 19 their subordinate criteria regarding new product development by literature review and expert interview. It employed the Interpretive Structural Model (ISM) to obtain the dimension-dimension and criterion-criterion dependence relationship, and used the Fuzzy Failure Mode and Effect Analysis (Fuzzy FMEA) to determine the top priority factor for assessment improvement in the new product development solutions of the enterprises.

As the competitive market nowadays shortens the life cycle of products, new products should be designed to meet the customer’s demand under a dynamic marketing environment so as to efficiently enhance the product strength of new products with maximization of profit. Hence, the key solution for enterprises to succeed will be the precise evaluation of new product development (NPD) performance, particularly for those who manage to survive in the intensely competitive market in Taiwan. This study is to identify the thin film transistor-liquid crystal display (TFT-LCD) touch panel industry and then establish an integrated model of NPD performance evaluation for enterprises. Firstly, literature review and interviews with experts are conducted to select the four aspects and 15 criteria as the main factors affecting NDP performance evaluation. Secondly, Decision Making Trial and Evaluation Laboratory (DEMATEL) is employed to identify the interrelationships among those factors. Finally, a Fuzzy theory is applied to resolve the linguistic hedges and an Analytic Network Process (ANP) is adopted to obtain the weights of all factors. A case study is performed to validate the proposed model in a Taiwanese TFT-LCD company. It not only provides the decision maker with a guidance system but also increases the competitive advantages for the TFT-LCD industry to design new products in the future.