Research Methods in Engineering

3Integrating Six Sigma


Integrating Six Sigma in a Manufacturing Process: A Case Study

1.0 Background of Research

Six Sigma is simply a measurement technique that aims to make the quality of products and services be better. It is a data-driven methodology and approach that aims at eliminating the defects in the industrial processes from transactional to manufacturing and from services to products. Six Sigma uses statistical tools to fight the variability that a company may be experiencing. All companies usually experience variation thus making Six Sigma critical. It allows the reduction of the variability in the company to the lowest state possible. Most of the project teams have models that assist in the integration of the Six Sigma. The models are in the form of manuals or guides that help resolve a problem in a company based on variation. According to Gitlow and Levine (2005), the most common strategy or model that the project teams use is the Define, Measure, Analyse, Improve, and Control abbreviated as DMAIC. The methods are based on a guideline that enables the project team to know when and what statistical tools to use. It also enables the statistical and other tools used in a manufacturing company to understand the project priorities as per the effect and variation associated with the processes.

2.0 Current State-of-the-art

Companies such as Sony, Kodak, General Electric, and Motorola Solutions have integrated the Six Sigma. As a result, they have managed to convince their potential and current customers that any of their services or products that they provide are of good quality (Pillai, Pundir & Ganapathy 2012). The major disadvantage of Six Sigma is that the process can be completed only after the problems associated with the quality of products and services are solved. The solution of the problems can be achieved with the purchase of technology, machinery, tools, or a given amount of investment (Pacheco 2014). However, some of these issues might be complex for small businesses. Other challenges of integrating Six Sigma in the manufacturing process are due to its possibility to a suite in several projects. As a result, it is hard to determine which project should be given priority when integrating the Six Sigma. It is also hard to determine the project that will go through a significant change based on the desire to reduce variability (Hassan 2013). Companies that have a limited budget, therefore, need to take a lot of consideration before engaging in the integration of Six Sigma.

3.0 Research Objectives and Hypothesis

The research will be based on three main objectives;

  1. To determine the suitable method that Six Sigma can be integrated into a manufacturing process

  2. To analyse how Six Sigma can be deployed in Constraints Management for the improvement of manufacturing companies

  3. To evaluate how Sigma Six can be integrated into manufacturing companies with limited resources

The study will be tested using through null hypothesis;

H01— Six Sigma cannot be efficiently integrated into the manufacturing process.

H02— Six Sigma cannot be integrated with the Constraints Management to improve the manufacturing process.

H03— Six Sigma cannot be implemented in manufacturing companies with limited with limited resources.

4.0 Research Methodology

The study will focus on an integrated model that focuses on improving a program in a manufacturing company. First, it will identify the constraints within the manufacturing industry and define them. Second, is the Critical Total Quality stage that will focus on measuring the efficiency of the processes (Ehie & Sheu 2005). Third, the movements, causes, or motions will be analysed followed by exploitation of the constraints. The process will then be verified and improved after which the constraint will be elevated (Niu, Lau, & Pecht 2010). Lastly, the inertia will be controlled and watched to ensure improvement keep working.

Reference List

Ehie, I & Sheu, C 2005, ‘Integrating six sigma and theory of constraints for continuous improvement: a case study’, Journal of manufacturing technology management, vol. 16, no. 5, pp.542-553.

Gitlow, HS & Levine, DM 2005,  Six Sigma for green belts and champions: foundations, DMAIC, tools, cases, and certification, Prentice Hall, Upper Saddle River, NJ.

Hassan, MK 2013, ‘Applying Lean Six Sigma for waste reduction in a manufacturing environment’,  American Journal of Industrial Engineering, vol. 1, no. 2, pp.28-35.

Niu, G, Lau, D & Pecht, M 2010, ‘Computer manufacturing management integrating lean six sigma and prognostic health management’, International Journal of Performability Engineering, vol. 6, no. 5, pp.453-466.

Pacheco, D 2014, ‘Theory of Constraints and Six Sigma: convergences, divergences and research agenda for continuous improvement’, Independent Journal of Management & Production, vol. 5, no. 2, pp.331-343.

Pillai, AKR, Pundir, AK & Ganapathy, L 2012, ‘Implementing integrated lean Six Sigma for software development: A flexibility framework for managing the continuity: change dichotomy’, Global Journal of Flexible Systems Management, vol. 13, no. 2, pp.107-116.