Integrating Six Sigma in Manufacturing - Literature review Example

Literature Review on Integrating Six Sigma in Manufacturing By: Professor: Class: University: City: State: Date of submission, Literature Review on Integrating Six Sigma in Manufacturing Table of Contents Table of Contents 2 Abstract 3 Implementation of Six Sigma 3 Six Sigma tools and techniques 5 Implementation of SS in SMEs vs. Big Companies 7 Integration of Constraints Management and the Six Sigma 12 Literature Gap 12 References 14 Abstract Six Sigma (SS) methodology is currently becoming one of the approaches preferred in the quality management considering the benefits it offers including ensuring the improvement of the output processes through identification and removal of various factors causing the defects and variability in both manufacturing and processing activities. Therefore, over the last decade, literature on the Six Sigma topic has been on the rise with the vast number of works undertaken on the topic representing a good opportunity for the structured literature review. The literature review has been undertaken through the chronological review of the major approaches of the SS developed for both the large and small institutions to improve the quality of their processes. Such focus is vital, as it tends to highlight a particular aspect of the SS literature and application of the SS methodology. The review of literature emphasized on the evaluation of the papers through the strength-weakness criterion. Implementation of Six Sigma According to Al-Mishari and Sulman (2008) businesses could employ three possible approaches in implementing the SS. The first method is the business transformation approach, which requires an organization to undergo a complete change involving transformation of the traditional methodologies of working for acquisition of the lost potential clients overcoming institutional massive losses. Strategic improvement is the second methodology; however, there is limitation to either one or two organizational critical needs while focusing on the main business opportunities and weaknesses. Problem-solving approach is the third approach is problem-solving approach which majorly concentrates of persistent challenges experienced by the business. In such regard, there are several publications suggesting the Design, Measure, Analyze, Improve, and Control (DMAIC) and the Design for Six Sigma (DFSS) method as the commonly used methodologies for implementing the SS. Nonetheless, Edgeman and Dugan (2008) cited that the two methodologies have different methodologies. Even though reasearchers consider DMAIC as a problem solving methodology aiming to enhance the processes, Watson and DeYong (2010) defines DFSS on the other hand as the process of defining, designing, and delivering innovative and quality products. Moreover, it is vital that the products provide attractive value considered competitive to the potential clients to achieve critical-to-quality characteristics for various vital functions. Therefore, focusing on the meaning of DFSS, it is evident that the approach is applicable within different contexts especially the new product development that majorly puts emphasis on the quality of the product from the beginning to the end (Edgeman & Dugan 2008). From such analysis, Aboelmaged (2010) holds that institutions enjoying steady growth of the market and the desired position in terms of competitive advantage would be in a better position with the integration of the DFSS considering the product development and innovation. However, the institutions experiencing stagnation in the market or considered incompetitive, DMAIC would be the favorable choice considering that it focuses on cost reduction, divestiture, and retrenchment. However, it is possible to deploy both the approaches simultaneously. As the general trend, competition is becoming too high that quality manufacturing and production processes are inevitable. As a result, many organizations are focusing on extending the DMAIC to include the DFSS (Aboelmaged 2010). The most possible reason for such practice is that several entities classically undertakes training for their workers on the DMAIC approach before expanding to the DFSS, which they tailor through the new product and service development context. In such regard, according to Banuelas and Antony (2004) the achievement of the figure of 3.4 parts per million in Six Sigma of defects in products and services redesigning and important processes through DFSS depends on an organizational commitment to quality processes. However, such argument is debatable considering that there is inadequate literature accepting or rejecting the hypothesis. According to Edgeman and Dugan (2008) DMAIC and DFSS mainly focus on the scientific methodologies. To certain extent, such methodologies are considered in different manners analogous to different approaches viewed as familiar and utilized in undertaking hypothetical testing and undertaking different experimental designs such as iterative. Moreover, several litureature undertaken reveal that there are variations in the DMAIC; however, the methodology remains commonly utilized. The variations are P-DMAIC (Project-DMAIC, DMAICR (DMAIC Report), and the E-DMAIC (Enterprise-DMAIC). The major factors that define the distinctions are based on the number and phase types but not the utilized tools. In the DMAICR, there is addition of reporting the benefits associated with the re-engineering process in the final step into the DMAIC (Senapati 2004). However, there are several variations as well. For example, the ICOV (Identify, Characterize, Optimize, and Verify), DMADV (Define, Measure, Analyze, Design, and Verify), DCOV (Design, Characterize, Optimize, and Verify), and IDOV (Identify, Design, Optimize, and Validate) show no significant distinctions. The selection criteria for the approach considered appropriate depends on specific requirements of the organization; nonetheless, some of the businesses implement Six Sigma at both the level of the project and the institution. In such cases, most organizations often prefer P-DMAIC or E-DMAIC methodologies. In their study, Watson and DeYong (2010) provided an inclusive chronological option methodologies to DFSS. Six Sigma tools and techniques According to Gitlow and Levine (2005) there are several tools applicable to Six Sigma projects accessible within both public and literature fields. Even though most these tools are known and applicable in different manufacturing processes and other organizational contexts, the Six Sigma in most cases provide a customer focused and properly defined methodology that is supported through the establishment of vivid set of inclusive tool meant to improve business processes (Van Iwaarden et al. 2008). DMAIC has tools applicable within the Yellow-Belt level for improving the level of competence. Some of the tools are check sheets, scatter diagrams, cause/effect diagram, flowcharts, statistical process control, and pareto-diagram. However, there are more advanced tools used in the SS including the regression analysis, hypothesis testing, design of experiments, and the control charts, which form the typical feature at the Black-Belt level. As a result, some researchers view Six Sigma as an integration of the existing tools and methodologies available before its development (Van Iwaarden et al 2008). According to Yeung (2007) there are different forms of Six Sgma tools including the analysis templates, procedures, and models. Moreover, the availability of such array of techniques tends to complicate the process, which makes it essential to have improvement tools for incorporation within the DMAIC process (Gitlow & Levine 2005). While embarking on any of the Six Sigma project, it is important to adapt and develop the tools the integration matures. Usually, the simple tools are significant in reducing the defects associated with the complexity of the manufacturing system within the early phases (Ehie & Sheu 2005). Although there are variations in tools and approaches, it is important to ensure the application of the appropriate situation with an aim of achieving the most successful results. Such factors tend to justify the ordinary practice within the literature to list the major tools at the early stages of the DMAIC methodology. Nonetheless, there is no standardized decision process of choosing the most appropriate tools within institutional context (Yeung, 2007; Van Iwaarden et al, 2008; Al‐Najjar & Kans 2006). Over the years, there have been inclusion of different tools by the company in the Six Sigma methodology with an aim of ensuring the effectiveness of the approach and eliminate the possible gaps after the application of the concept on the organization. These tools include those from industrial engineering and the field of operations research. There are differences in the tools used in both DMAIC and DFSS. In a research undertaken by Ehie and Sheu (2005) the revealed that DFSS mainly involve the innovation tools including integration of the creative problem solving theory and axiomatic design. During the review, one notable observation involve using the simulation technique within the improve phase. In the modern research, the major tool requiring special mention as the emerging methodology is simulation that could play important role in various Six Sigma initiatives and ensure the achievement of the long-term proseperity. The major factor that has contributed to the emergence of powerful simulation packages is the evolution of the computer hardware for the Analyze and Improve stages. Moreover, such evolution allows saving within the design experiment phase through testing the solutions before the implementation. According to Al‐Najjar and Kans (2006) simulation in manufacturing process has been successful in the past twenty years on its own; however, it has not shown signs of being complementary to the SS, as few articles tend to address the incorporation of the tool and approach. Besides, the situation changed as researchers like McCarthy and Stauffer (2001) stated that Six Sigma has been in a position of delivering significant results without incorporation of the simulation tools. To some extent, the researchers agree that incorporation of simulation if the SS could make it even more successful in the future. Implementation of SS in SMEs vs. Big Companies Implementation of various SS tools within the organization requires adequate resources. Although the SMEs are considered more flexible that larger institutions, they have limited resources which could make it difficult to implement the SS. Considering the nature of SMEs, it is easy to introduce the changes. In addition, within the SMEs, there is high visibility of the top management and better predisposition to the final consumer, which represent one of the fundamental bases of the total quality management. The close relationship between the management and employees and the extent of communication with the customers within the SMEs appear to be significant for the SMEs compared to large institutions (Al‐Najjar & Kans 2006). The SMEs could use the DMAIC procedures although there are some differences. Besides, considering their impossibility of meeting the high cost associated with the implementation and unavailability of the full time experts within the SMEs. Therefore, the SMEs are forced to utilize simple statistical tools including the process mapping, cause and effect analysis, FMEA (Failure Mode and Effects Analysis), and histograms while missing the complex techniques that large companies with adequate resources tend to enjoy. Moreover, the decisions within the SMEs are made based on the short-term profitability and in most cases, there are no incentives programmes considering that such institutions have constraints in their budgets and resources. SMES experience unavailability of trained experts making extensive training cost prohibitive and the objective of developing sparing personnel to become Black Belt is unrealistic. It is possible to integrate SS with the other quality management models (Gitlow, Levine & Popovich 2006). However, the common error is consideration of the SS as a complete replacing model. Moreover, most of the companies are apathetic on the SS considering that they tend to believe in their existing cultural systems including ISO 9000 and continuous improvement, which they consider adequate in meeting the needs. Therefore, the SS should not replace the already existing organizational quality management systems through it could assist in improving them through getting into the institution. In most cases, the SMEs focus on the strategic improvement that involves addressing one or two areas within the business considered highly critical (Gitlow, Levine & Popovich, 2006). However, such approach is not extensive considering that the business transformation takes place more often and could be viewed as the “middle of the road” approach. An institution with limited approach could utilize strategic improvement approach. Business might wish to prove the application of the SS in a pilot project before expansion to other sectors. Figure 1: FMEA Mapping Integration of Constraints Management and the Six Sigma The constraint theory converted from the manufacturing scheduling method to the philosophy of management focusing on the improvement of the system. Spector (2006) explained the theory using the chain citing that the chain is worth the strength of the weakest link found irrespective of if the other links are strong enough, as the system would break whenever there is an insertion of the weakest link. The constraint theory suggests that the weakest links tend to exist within the top management and controlled to the point that everything works around. Although SS and constraints management tend to thrive in different philosophies, different organizations tend to complement one of the methodologies in their business and integrate both methodologies in solving their needs. With such integration, the organization could use SS in solving the complex problems, which require deep solutions; on the other hand, the organization could use constraint management in unveiling the bottlenecks within the system and ensuring adequate expansion. According to Al‐Najjar and Kans (2006) the common integration that the two disciples use consists of identification of the organizational constraint; however, upon locating the system with SS, it would take over the link and ensuring reduction in the variations and resolving organizational problems. Such methodology makes sense from the system point of view with the bottleneck being the first area of the SS project putting its interest considering that it is the area affecting the profit and the success of the project. Literature Gap According to the reviewed literature, there are four distinct interpretations of Six Sigma: set of statistical tools, analysis of the methodology using scientific methods, business culture, and operational philosophy of management; however, there is mutual exclusiveness and overlapping of the streams. There are two major principle approaches of implementing SS which depends of the purpose: DMAIC and DFSS, which are used in the improvement of processes and for the new development of product and services respectively. The literature tends to prove a variety of tools and techniques whose classification falls within the DMAIC methodology; however, there is little information on their application. The fundamental tools in most case are sufficient for the improvement of processes that organizations consider vital; nonetheless, the simulation technique usually opens new and promising avenue of improving the advantages associated with SS. The numerous of tools available in most cases result in the confusion especially while choosing the tools that work best within the manufacturing process. The existing literature, on the other hand, tend to categorize the various Six Sigma tools based on the DMAIC; however, the alternative approach to the DMAIC including DFSS, DMADV, and DCOV lack such tools of classification. References Aboelmaged, M. G. (2010). Six Sigma quality: a structured review and implications for future research. Int J Qual & Reliability Mgmt, 27(3), 268-317. Al‐Mishari, S. T., & Suliman, S. (2008). Modelling preventive maintenance for auxiliary components. Journal of Quality in Maintenance Engineering, 14(2), 148-160. Al‐Najjar, B., & Kans, M. (2006). A model to identify relevant data for problem tracing and maintenance cost‐effective decisions. Int J Productivity & Perf Mgmt, 55(8), 616-637. Antony, J., & Banuelas, R. (2002). Key ingredients for the effective implementation of Six Sigma program. Measuring Business Excellence, 6(4), 20-27. Edgeman, R. L., & Dugan, J. P. (2008). Six Sigma from products to pollution to people. Total Quality Management & Business Excellence, 19(1-2), 1-9. Ehie, I., & Sheu, C. (2005). Integrating six sigma and theory of constraints for continuous improvement: a case study. Journal of Manufacturing Technology Management, 16(5), 542-553. Gitlow, H. S., & Levine, D. M. (2005). Six sigma for green belts and champions: Foundations, DMAIC, tools, cases, and certification. Upper Saddle River, NJ: Pearson/Prentice Hall. Gitlow, H. S., Levine, D. M., & Popovich, E. A. (2006). Design for six sigma for green belts and champions: Applications for service operations--foundations, tools, DMADV, cases, and certification. Upper Saddle River, NJ: Pearson Prentice Hall. Senapati, R. N. (2004). Six Sigma: myths and realities. Int J Qual & Reliability Mgmt, 21(6), 683-690. Spector, R. (2006). How constraints management enhances lean and six sigma. Supply Chain Management Review, 10(1), 42-47. McCarthy, B., & Stauffer, R. (2001). Enhancing Six Sigma through simulation with iGrafx Process for Six Sigma. Proceeding of the 2001 Winter Simulation Conference , 2(1), 105-110. Van Iwaarden, J., Van der Wiele, T., Dale, B., Williams, R., & Bertsch, B. (2008). The Six Sigma improvement approach: a transnational comparison. International Journal of Production Research, 46(23), 6739-6758. Watson, G. H., & DeYong, C. F. (2010). Design for Six Sigma:caveat emptor. International Journal of Lean Six Sigma, 1(1), 66-84. Yeung, S. M. (2007). Integrating ISO 9001:2000 and Six Sigma into organisational culture. International Journal of Six Sigma and Competitive Advantage, 3(3), 210. Read More

To certain extent, such methodologies are considered in different manners analogous to different approaches viewed as familiar and utilized in undertaking hypothetical testing and undertaking different experimental designs such as iterative. Moreover, several litureature undertaken reveal that there are variations in the DMAIC; however, the methodology remains commonly utilized. The variations are P-DMAIC (Project-DMAIC, DMAICR (DMAIC Report), and the E-DMAIC (Enterprise-DMAIC). The major factors that define the distinctions are based on the number and phase types but not the utilized tools.

In the DMAICR, there is addition of reporting the benefits associated with the re-engineering process in the final step into the DMAIC (Senapati 2004). However, there are several variations as well. For example, the ICOV (Identify, Characterize, Optimize, and Verify), DMADV (Define, Measure, Analyze, Design, and Verify), DCOV (Design, Characterize, Optimize, and Verify), and IDOV (Identify, Design, Optimize, and Validate) show no significant distinctions. The selection criteria for the approach considered appropriate depends on specific requirements of the organization; nonetheless, some of the businesses implement Six Sigma at both the level of the project and the institution.

In such cases, most organizations often prefer P-DMAIC or E-DMAIC methodologies. In their study, Watson and DeYong (2010) provided an inclusive chronological option methodologies to DFSS. Six Sigma tools and techniques According to Gitlow and Levine (2005) there are several tools applicable to Six Sigma projects accessible within both public and literature fields. Even though most these tools are known and applicable in different manufacturing processes and other organizational contexts, the Six Sigma in most cases provide a customer focused and properly defined methodology that is supported through the establishment of vivid set of inclusive tool meant to improve business processes (Van Iwaarden et al. 2008). DMAIC has tools applicable within the Yellow-Belt level for improving the level of competence.

Some of the tools are check sheets, scatter diagrams, cause/effect diagram, flowcharts, statistical process control, and pareto-diagram. However, there are more advanced tools used in the SS including the regression analysis, hypothesis testing, design of experiments, and the control charts, which form the typical feature at the Black-Belt level. As a result, some researchers view Six Sigma as an integration of the existing tools and methodologies available before its development (Van Iwaarden et al 2008).

According to Yeung (2007) there are different forms of Six Sgma tools including the analysis templates, procedures, and models. Moreover, the availability of such array of techniques tends to complicate the process, which makes it essential to have improvement tools for incorporation within the DMAIC process (Gitlow & Levine 2005). While embarking on any of the Six Sigma project, it is important to adapt and develop the tools the integration matures. Usually, the simple tools are significant in reducing the defects associated with the complexity of the manufacturing system within the early phases (Ehie & Sheu 2005).

Although there are variations in tools and approaches, it is important to ensure the application of the appropriate situation with an aim of achieving the most successful results. Such factors tend to justify the ordinary practice within the literature to list the major tools at the early stages of the DMAIC methodology. Nonetheless, there is no standardized decision process of choosing the most appropriate tools within institutional context (Yeung, 2007; Van Iwaarden et al, 2008; Al‐Najjar & Kans 2006).

Over the years, there have been inclusion of different tools by the company in the Six Sigma methodology with an aim of ensuring the effectiveness of the approach and eliminate the possible gaps after the application of the concept on the organization.

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