Lean design for Six Sigma

Abstract

Purpose– The purpose of this paper is to discuss new product development (NPD) based on a traditional stage-gate process and to examine how NPD tools, such as Lean design for Six Sigma, can accelerate the achievement of the main goals of NPD: reliable product quality, cost-effective implementation, and desired time-to-market. These new tools must be incorporated into a new approach to NPD based on the Advanced Product and Quality Planning methodology.Design/methodology/approach– This research paper is based on the theoretical background presented in peer-reviewed scientific research papers during the period 1990-2012. In the second section of this study, the author provides examples of the proposed tools and of advanced techniques to show evidence that validates the hypothesis.Findings– This study presented the theoretical background on the NPD process and related functions in today’s organizations as it relates to competition. NPD was identified as one of the top priorities of every firm, which is why the NPD process must be optimized and oriented toward customers to ensure the quality and reliability of products while minimizing manufacturing costs. The effect on timing and cost is greatly appreciated by top management, and it is well known throughout the firm when a strong, reliable product is launched that it is flawless.Research limitations/implications– To fully deploy all NPD tools requires basic steps such as the following: marketing and planning, design, process, product process validation and the integration of operations from a concurrent engineering standpoint.Practical implications– This research paper provides step by step guidance in order to apply Lean Sigma tool in NPD process in order to achieve Six Sigma quality level in manufacturing.Social implications– Promoting the practice of Lean design for Six Sigma and its tool enables firms to increase their competitiveness since they will make more reliable products delivered to its consumers.Originality/value– The approach of this research paper combines proven statistical tools to be applied in an original sequence in order to design robust product to match manufacturing capabilities.