Agility assessment in new product development for an electronics manufacturing company.

• Main Authors: Phong, Wei Loon, Wong, Kuan Yew
• Format: Conference or Workshop Item
• Published: 2023
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/107312/; https://doi.org/10.1063/5.0177716

Agility evaluations are commonly used in various industrial settings for various businesses. The demand for advanced and innovative electrical items has skyrocketed in recent years. As a result, management decided to investigate the present agility performance in an electronic manufacturing company's product development process to drive and meet client demand. The organisation cannot define the necessary measures that may be used for agility performance due to a lack of understanding in analysing agility performance for the product development process. Because agility cannot be defined using a quantitative method by its subjective and vague linguistic description, a fuzzy inference system-based model is developed to evaluate agility performance in the product development process. The product development process's agility metrics are defined, and survey questions are created accordingly. Expert survey responses are in the form of linguistic variables. As a result, the Mamdani fuzzy inference system (FIS) use MATLAB to calculate membership function grades and linguistic phrases for various agility levels. Furthermore, If-then fuzzy rules are utilised to collect and add the relationship between agility measures based on experts' expertise while dealing with challenges of uncertainty and vagueness. The generated crisp output results for metrics and overall agility performance are valuable suggestions for company management to examine and determine which metrics should be prioritised for product development agility enhancement. The overall agility score in the product development process is 4.52, which is marginal average. Therefore, agility improvements are needed to adapt quickly to unknowns and unforeseen shifts in client demand while maintaining cost and quality control.