A case study on FMEA-based quality improvement of packaging designs in the TFT-LCD industry

Abstract

Nowadays enterprises are encountering diversified customer requirements, and using market information well is critical to product development. It is extremely important to conduct risk planning, prevent potential failures, and reduce uncertain factors by transforming customer requirements into exact development targets. This study is based on the method of quality function deployment (QFD) and failure modes and effects analysis (FMEA). The package design for semi-finished products of thin film transistor-liquid crystal display (TFT-LCD) modules in the photoelectricity industry was selected as a case study. First, customers conducted a questionnaire survey which helped determine the items they demanded. Second, QFD has been combined with FMEA to serve as the standard of evaluating the importance of customer requirements. Through mutual assessments and investigations by QFD and design failure mode and effects analysis (DFMEA), the key factors of a product design can be determined. The results of design of experiments verified that this method indeed effectively reduced defective products and customer complaints. The average number of customer complaints per year has been reduced from 9.5 to just only one after the introduction of the proposed method, which has been verified to assist in rapidly developing new products during the early design stage. This approach also reduces possible losses and enhances competitiveness.

A case study on FMEA-based improvement for managing new product development risk

“…After implementing preventive and corrective measures, the results demonstrate that FMEA helps decrease the risk of future failures, which is in line with previous findings (Liu et al, 2016;Yeh et al, 2010). Overall, the RPN decreased by 69% after implementing FMEA.…”

The Risk Priority Number Evaluation of FMEA Analysis Based on Random Uncertainty and Fuzzy Uncertainty

“…For instance, the intuitionistic fuzzy weighted averaging (IFWA) operator [21], the fuzzy AHP method in [29], the triangular intuitionistic fuzzy entropy method [30], the three-dimensional geometric approach to fuzzy weighted Euclidean (FWE) FMEA, the IVIF MUL-TIMOORA method [31], and even the integrated method by extended fuzzy AHP and fuzzy MULTIMOORA [32] are all these types of typical studies. Cost [4,6,7,24], customer demand [33,34], and quality [7] are integrated into FMEA to solve the third shortcoming in many studies. For the fourth shortcoming of traditional FMEA, the Bayesian network (BN) method [16,[35][36][37][38][39] is the most common solution, and other methods include fuzzy cognitive maps [1], FTA analysis [25], and DEMATEL [40][41][42].…”

Product Quality Analysis of Pia Edamame Using Quality Function Deployment Method

“…Pia edamame SR, therefore, needs a new packaging design. Liu et al (2016) also mentioned that changing the packaging as the result of QFD analysis is able to reduce consumer complaint and increase product's competi-tiveness. Additionally, Vanany, Maarif, & Soon (2019) have obtained from the analysis of QFD that program development priority is able to provide effort to company in decision making and allocation of existing resources.…”