B. Tjahjono, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
P. Ball, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
V.I. Vitanov, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK School of Engineering and Computer Sciences, Durham University, Durham, UK
C. Scorzafave, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
J. Nogueira, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
J. Calleja, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
M. Minguet, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
L. Narasimha, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
A. Rivas, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
A. Srivastava, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
S. Srivastava, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
A. Yadav, Manufacturing Department, School of Applied Sciences, Cranfield University, Cranfield, UK
Purpose – The purpose of the work presented in this paper is to capture the current state of Six Sigma as well as to document the current practices of Six Sigma through a systematic literature review so as to extend and update the previous work of Brady and Allen.
Design/methodology/approach – The approach to this paper is to answer the questions such as “what is Six Sigma?”, “what are the applications of the Six Sigma?”, “what are the main enablers and barriers to its application?” and “what are the emerging trends?” These questions are used to guide the search of papers from various publication databases even if it is expected that existing literature might not be sufficiently developed to translate each question directly into a finding. The literature is then analysed and the major emerging themes are presented.
Findings – Seven key findings (topics on which the views of the authors converged) and two issues (topics on which authors had differing views) have been established. These include the interpretation of Six Sigma, tools and techniques, implementation of Six Sigma, benefits, adoption, enablers and links to other disciplines.
Originality/value – The systematic literature review approach used in this paper allows emerging trends and issues in Six Sigma to be highlighted in a structured and thematic manner, enabling the future work to progress as Six Sigma continues to develop and evolve. The findings also open up new opportunities to apply Six Sigma in the fields that are not widely explored before for instance sustainability and product-service systems.
Six Sigma; Production processes.
International Journal of Lean Six Sigma
Emerald Group Publishing Limited
Since the introduction of the initial six-step process by Motorola University Design for manufacturing training programme in 1988 (Watson and deYong, 2010), Six Sigma has evolved to become an extension to total quality management (TQM) (Green, 2006). As a project-driven management approach, the range of Six Sigma applications is also growing from reduction of defects in an organisation's processes, products and services to become a business strategy that focuses on improving understanding of customer requirements, business productivity and financial performance (Kwak and Anbari, 2006). Six Sigma has branched out initially from the electronics industries (e.g. Motorola and Texas Instruments) to many other sectors. In the last two decades, this growth has become more prevalent as Six Sigma principles have also been implemented in service industries in the context of supply chain (Arnheiter and Maleyeff, 2005; Wei et al., 2010), as well as hospitals (Sehwail and DeYong, 2003; van den Heuvel et al., 2005), local government (Furterer and Elshennawy, 2005) and public sectors (Patel and Zu, 2009; Kumar and Bauer, 2010).
The purpose of this paper is therefore to capture the state of the art within the Six Sigma philosophy as well as to document notable development of practices through a systematic literature review. The methodology includes targeting relevant publications databases, searching these using a wide range of keywords and phrases associated with Six Sigma and then reviewing each paper identified. The outcome of these reviews was the extraction of a set of key findings, compiled and grouped by topics.
2 Research programme
2.1 Scope and research questions
This review of literature, to a large extent, aims to extend the work of Brady and Allen (2006) who incorporated Six Sigma publications from 1990 to 2003 and complement their findings. For this reason, the systematic literature review in this paper considers a defined time frame from 2004 to 2009. To provide a global vision of the subject matter, the scope of this work is not limited in terms of the industrial sectors considered but only in terms of the type of sources used, i.e. from journal publications from established databases.
The initial approach to this research was to answer the following questions:
RQ1. What is Six Sigma?
RQ2. What are the applications of the Six Sigma?
RQ3. What are the main enablers and barriers to its application?
RQ4. What are the emerging trends?
The purpose of these questions was to guide the search even if it was expected that existing literature might not be sufficiently developed to translate each question directly into a finding.
2.2 Search strategy
The search strategy was developed by first identifying the relevant data sources and keywords. The databases included Scopus, ABI/Inform, IEEE Xplore and Emerald. The time frame was chosen initially to include only the literature published between 2004 and 2009, however, as the research progressed, this was extended as a result of cross citations to include papers from 2000.
The search is set out by choosing a set of keywords and possible combinations that could be significant to Six Sigma. The concept of Six Sigma embraces a very wide range of aspects and so a considerable number of search strings were deemed necessary. These captured all the aspects that characterise Six Sigma, such as definition, methodology, techniques, tools, implementation, enablers and issues. Keywords related to other important concepts to analyse possible connections were also used. Examples of these include lean, supply chain management, process management and sustainability.
Table I shows the number of items associated with some of the search strings used. It shows the publications related to the implementation of Six Sigma, the associated tools and techniques and the design, measure, analyse, improve, control (DMAIC) methodology. Also quite developed in literature is the topic of “lean and Six Sigma”. Perhaps, surprisingly, the keywords “Six Sigma+sustainability” only retrieved 12, although the concept of sustainable production was presented almost 30 years ago (Miron and Skarke, 1981).
The main exclusion criterion in this search was to take into account only papers focused primarily on Six Sigma, ignoring consequently the ones that cited it as methodology used but did not go in depth in the dissertation about it.
2.3 Results and analysis
The search strategy initially identified 210 publications. However, each work was checked by first reading the abstracts so that those that appeared to be outside the scope of the review, because of the vagueness and lack of detail for instance, were excluded. Following the screening, the papers were reduced to 167 as a result from more thorough examination to derive the main contents. By analysing the authorships of those papers (Figures 1 and 2) it can be seen how the interest is roughly equally distributed between industry and academia, and how the applications of Six Sigma in the service sector are becoming more prevalent. After this step, 76 publications were identified as being available and suitable for the present work and an analysis was conducted on these particular papers because of the higher level of detail offered compared to the rest of the papers. The results of these search help provide the following series of key findings.
3 Generation of key findings
The literature review established seven key findings (topics on which the views of the authors converged) and two principal issues (topics on which authors had differing views). This section presents each of them.
3.1 Definition of Six Sigma
From the various definitions found in the reviewed publications, it was possible to identify at least four streams of thought of Six Sigma.
The first stream defines Six Sigma as a set of statistical tools adopted within the quality management to construct a framework for process improvement (Goh and Xie, 2004; McAdam and Evans, 2004). The objective is to enhance the Six Sigma level of performance measures referred to as the critical to quality (CTQ) which reflects the customer requirements through a group of tools for the analysis of the data. Statistical tools identify the main quality indicator which is the parts per million (PPM) of non-conforming products (Mitra, 2004). Achieving a Six Sigma level means having a process that generates outputs with <3.4 defective PPM (Coleman, 2008; Anand et al., 2007). Here, Six Sigma is recognised as a problem-solving method that uses quality and statistical tools for basic process improvements but not necessarily a comprehensive management system.
The second stream defines Six Sigma as an operational philosophy of management which can be shared beneficially by customers, shareholders, employees and suppliers (Chakrabarty and Tan, 2007). Thanks to its flexibility, Six Sigma application is not limited only to manufacturing but can be extended to the whole supply chain which includes the provision of services. It is, according to Yang et al. (2007), useful to enforce a more disciplined approach towards supply chain projects to define and execute them more rigorously. Six Sigma is also defined as a multifaceted, customer-oriented, structured, systematic, proactive and quantitative philosophical approach for business improvement to increase quality, speed up the deliveries and reduce costs (Mahanti and Antony, 2005).
The third stream defines Six Sigma as a business culture. This stream argues that the success of Six Sigma does not rely only on statistical tools and techniques but also on the commitment of the top management to guarantee the involvement of the employees in the organisation. Markarian (2004) considers Six Sigma as a rigorous top-down methodology which demands detailed analysis, fact-based decisions and a control plan to ensure ongoing quality control of a process. This organisational aspect is also shown in the work of Pheng and Hui (2004), who define Six Sigma as a “cultural and belief” system which guides the organisation in repositioning itself towards world-class business performance by enhancing factual decision making. Similar definition is given by Schroeder et al. (2008) who consider Six Sigma as an organised structure using process improvement specialists with the aim of achieving strategic objectives.
The fourth definition refers Six Sigma as an analysis methodology that uses the scientific methods. Banuelas and Antony (2004) and Thawani (2004) consider it as a well-structured continuous improvement methodology to reduce process variability and remove waste within the business processes. Black and Revere (2006) support this by claiming Six Sigma as a popular and widely used quality improvement methodology. Kumar et al. (2007) argue that Six Sigma is an extension to quality improvement initiatives such as the TQM because of the similarities between the Six Sigma method of DMAIC and the Deming's plan, do, check and act. Using the DMAIC method sequentially can help integrate human aspects (culture change, training and customer focus) and process aspects (process stability and capability, variation reduction) within the Six Sigma implementation (Antony et al., 2005b):
Finding 1. Four interpretations of Six Sigma have been identified in the literature as a set of statistical tools, an operational philosophy of management, a business culture and an analysis methodology that uses the scientific methods, although the streams are not mutually exclusive but instead, overlapping.
3.2 Six Sigma implementation
Al-Mishari and Suliman (2008) suggest three possible “on-ramps” or approaches an organisation can take to implement Six Sigma. The first is through a business transformation approach where an organisation undergoes complete change to convert its traditional method of working in order to regain lost customers or to overcome the heavy losses. The second is the strategic improvement approach limited to one or two critical business needs focusing on major opportunities and weaknesses. The third is a problem-solving approach which focuses only on persistent problems.
In this respect, many of the publications suggest the DMAIC and the design for Six Sigma (DFSS) methods as the two most common methodologies to implement Six Sigma, although according to Edgeman and Dugan (2008), the main objectives of the two techniques are quite different.
While DMAIC is a problem-solving method which aims at process improvement, DFSS is defined by Watson and deYong (2010) as “a process to define, design and deliver innovative products provide competitively attractive value to customers in a manner that achieves the critical-to-quality characteristics for all the significant functions”. It is therefore clear from this definition that DFSS is used in the context of new product development that focuses on quality from the very beginning (Edgeman and Dugan, 2008). To this end, Mader (2006) believed that companies with strong market growth and competitive position will be better off with DFSS (focusing on product development and innovation), whereas for companies with stagnant market or relatively less competitive, DMAIC is generally a more favourable choice focusing on cost reduction, retrenchment or divestiture.
Deploying the two approaches in different parts of the business simultaneously is possible, even if most of the publications reviewed presented the case studies based on either of them. As a general trend, many organisations have now extended DMAIC to include DFSS (Mader, 2006). Possible reason is that many companies typically train their employees in DMAIC first then expand it to DFSS which is tailored to the context of new product and/or service development. In this respect, Banuelas and Antony (2004) stated that in order to achieve the Six Sigma figure of 3.4 PPM of defects is to redesign products, key processes and services by means of DFSS. This argument is, however, debatable as no literature clearly accepts or rejects this hypothesis. Nonetheless, Edgeman and Dugan (2008) argue that both DMAIC and DFSS are firmly rooted in the scientific method and are in many ways analogous to the familiar approaches used either by the hypothesis testing or the iterative experimental design.
The literature further shows that there are several variations for DMAIC (even if it remains the most commonly adopted methodology) such as Project-DMAIC (P-DMAIC), Enterprise-DMAIC (E-DMAIC) and DMAIC Report (DMAICR). The differences are mostly in terms of the number and type of phases, rather than the tools used. DMAICR, for instance, adds the final step of “reporting the benefits of the re-engineered process” into DMAIC (Senapati, 2004). Numerous variations of DFSS also exist, for example, define measure analyse design verify (DMADV), design characterise optimise verify (DCOV), identify design optimise validate, identify characterise optimize verify and DMADV, but in this case, there are no significant differences amongst them. The selection of the methodology, in the end, depends on the specific requirements (Chakrabarty and Tan, 2007) and some companies implement Six Sigma not only at the project level but also at the enterprise level (Ward et al., 2008). In these instances, either P-DMAIC or E-DMAIC approach is generally used (Breyfogle, 2008). Watson and deYong (2010) provide a comprehensive chronological alternative approaches to DFSS:
Finding 2. Depending on the purpose, there are two principal methodologies in which Six Sigma can be implemented: DMAIC and DFSS. DMAIC is generally used for process improvement and DFSS for new development of product and services. Literature presents many variations of both.
3.3 Tools and techniques of Six Sigma
Many tools and techniques that can be applied to Six Sigma projects are available both in the literature and public domain (Halliday, 2005). Although most of these tools are already well known and applied in other contexts, Six Sigma provides a customer focused, well-defined methodology supported by a clear set of comprehensive tools for process improvement (van Iwaarden et al., 2008). Basic tools of DMAIC, typically used at the yellow-belt level of competence include flowcharts, check sheets, Pareto diagrams, cause/effect diagrams, scatter diagrams, histograms and statistical process control (Ferrin et al., 2005). More advanced tools such as regression analysis (e.g. with indicator variables, curvilinear regression and logistic regression), hypothesis testing, control charts and design of experiments typically feature at the black-belt level. This also means Six Sigma may be viewed as a combination of existing tools and techniques available well before Motorola developed this approach (van Iwaarden et al., 2008).
Tools are also available in various forms such as models, analysis templates and procedures (de Koning and de Mast, 2006) and it is this wealth of techniques that complicates the process, making the need of a robust set of what are essential improvement tools to be used within the DMAIC process more obvious (Brady and Allen, 2006). One important aspect to consider when embarking any Six Sigma project is that tools will have to adapt and develop as the project matures. Often, simple tools are enough to reduce the defects of a complex manufacturing system in the initial stages (Raja, 2006).
Even though tools and techniques vary, it is essential to apply the right tool in the right situation in order to achieve successful results. This perhaps justifies why it is a common practice in the literature to catalogue the main tools within the five phases of the DMAIC approach. However, there is an absence of standardised decision procedures to choose the most appropriate tools in a specific context (Hagemeyer et al., 2006; Kumar, S. et al., 2008; Williams, 2009; de Koning et al., 2008). Likewise, as put forward by Brady and Allen (2006), finding literature that provides methods for specific projects and the associated financial results is often difficult because of the confidentiality reasons.
Over the years, companies have included numerous tools into the Six Sigma approach to make them more effective and to eliminate possible gaps after its application. Such toolsets include statistical and analytical tools both from industrial engineering and operations research fields (Bunce et al., 2008). In this instance, these tools enrich the practical and industrial approach with a stronger theoretical basis to achieve a better equipment and resources utilisation (Maciel Junior et al., 2008).
The tools within the DFSS methodology are usually different from those of the DMAIC. Chakrabarty and Tan (2007) claim that DFSS typically includes innovation tools such as the theory of creative problem solving and axiomatic design which DMAIC does not, although it could.
One notable observation during the review was the use of simulation techniques within the “improve” phase. Although not part of the keyword search, the use of simulation is commonly referenced in the papers but does not consistently appear in the tool categorisation lists. Simulation is one of the tools deserving special mention as an emerging technique that can play an important role in Six Sigma initiative today and is considered by some authors, for example McCarthy and Stauffer (2001), to be “vital to the long-term success of Six Sigma projects”. The evolution of computer hardware has enabled the use of powerful simulation packages for analyse and improve stages, as it allows significant savings in the design of experiments phase by testing solutions before implementation (Gladwin, 2003). Simulation has been very successful on its own for the past 20 years but this tool was not seen as complementary to Six Sigma and only few articles addressed the combination of such tool and methodology. This is no longer the case today, and although still few, some authors such as McCarthy and Stauffer (2001) state in their text that Six Sigma has already delivered significant results without the benefit of simulation but agree that simulation could make Six Sigma even more successful in the coming years:
Finding 3. The literature provides a wealth variety of tools and techniques which are often classified within the DMAIC approach but with little detail on specific examples of their applications. Basic tools are often sufficient for the initial improvements of most processes but the simulation techniques open up a new and promising avenue to enhance the merits already achieved by Six Sigma.
Issue 1. The variety of tools available sometimes causes confusion as to which tools work best for specific business requirements. Existing literature also categorises the Six Sigma tools based under DMAIC, however, alternative approaches such as DFSS, DCOV or DMADV lack this classification of tools.
3.4 Benefits of Six Sigma
Reduced costs, reduced project time, improved results and improved data integrity are some of the benefits of Six Sigma suggested by Ferrin et al. (2005). In addition, the literature tends to analyse the techniques used to optimise the process performance. The approach taken in many cases, e.g. by Lin et al. (2008) and Antony et al. (2005a), is to give the solutions and the methods built by Six Sigma to achieve sensible improvements, providing a learning process for managers in order to take a wide view of the system and change effectively the business (Thawesaengskulthai and Tannock, 2008). There are many benefits that can be derived from the adoption of Six Sigma. It could enhance product development cycles and process design, shorting product lead times by reducing the cycle time of the overall manufacturing process. Six Sigma can be used to find and eliminate the root causes of the problem, so reducing the variability in the process in order to prevent defects.
There are also organisational implications. Indeed, Six Sigma methodologies provide guidelines which could help the workers understand how to carry out the job and train them to solve potential problems. As a consequence, they become more aware of the production process thereby improving their morale and reducing the human-related defects (Hong et al., 2007). With respect to the role of Six Sigma in reducing the defects, it has been demonstrated in several studies that the defect rate per unit is reduced after its implementation in manufacturing systems (Kumar et al., 2006).
The adoption of Six Sigma has improved both the efficiency of the line and the production capability, including minimising waste such as reduced need for inspection, removed useless components and excessive movements and decreased time for repair (Oke, 2007). For this reason, Six Sigma can be used to build predictive models based on experiences gathered from earlier uncorrected measures to ensure a continuous improvement of the process (Johnston et al., 2008). In recent years, knowledge management has contributed to facilitate the implementation of Six Sigma and has emerged as a source of competitive advantage within the businesses (Gowen et al., 2008). Six Sigma is also recognised as a strategy that drives the cultural change to improve profitability of the company increasing the benefits from savings generated when the defect is detected at a very early stage (Antony et al., 2005a). However, van Iwaarden et al. (2008) state that the approach to Six Sigma varies between organisations because they integrate different techniques according to their needs, so there might be disagreement regarding the benefits as they depend on the industry and even the country where Six Sigma is applied.
Six Sigma also helps improve the relationships outside and within the organisation (Kumar et al., 2006). It can strengthen the customer loyalty by satisfying their needs and expectations and it works as a direct link to company's management which helps establish a common language from the board to the shop floor:
Finding 4. Six Sigma has many benefits and, unsurprisingly, the most frequently cited are the reduction and prevention of defects which affect the quality of both products and processes.
3.5 Six Sigma adoption
Over time, Six Sigma has developed and undergone significant changes. It initially applied in the manufacturing sector but has now spanned over service and financial sectors (Aghili, 2009). Antony (2007) grouped these changes into three generations. The first generation of Six Sigma (1987-1994) was focused on reduction of defects and saw success with Motorola. The second generation (1994-2000) was concentrated on cost reduction and was adopted by companies such as General Electric, Du Pont and Honeywell. The third generation (2000 onwards) is oriented to creating value for the customers and the enterprise itself and finds its application within companies like Posco and Samsung. This is more oriented to service and commercial business processes including transactional systems quality, which takes into account delivery times, customer waiting time to receive services, inventory service levels, etc.
Although the application of Six Sigma in service sectors is growing, the majority of the publications reviewed discuss the implementation and the problems encountered within the manufacturing sectors. Possible explanation of this is, according to Hensley and Dobie (2005), the service sector is dealing with intangible entities such as customer service, i.e. providing the assistance necessary to establish good relationships with them and aiming at an efficient communication to meet their expectations, where the success is more difficult to quantify. On the contrary, in the manufacturing sectors where an automatic data collection is used, for example in assembly lines, measuring the impact of the quality control programme is much easier to do. Furthermore, large organisations tend to initially introduce Six Sigma in their manufacturing facilities. Only after enhancing their knowledge about the tools and techniques to adopt, they gradually spread it to the service operations.
Literature also shows there is a different level of interest shown in the Six Sigma adoption not only in terms of type of operations (manufacturing or service) but also in terms of company size. In particular, multinational companies are often reported to have reaped the full benefits of Six Sigma. However, because of the project-based approach in DMAIC, small and medium enterprises (SMEs) should also benefit from it (Antony et al., 2005a).
It also emerged that many large companies, e.g. Xerox, Fidelity Investments, integrate Six Sigma with other techniques such as lean (Ranch, 2006; Hensley and Dobie, 2005), quality management system (Morgan and Brennig, 2006) and Kaizen/continuous improvement, e.g. Caterpillar (Haikonen et al., 2004). This shows how the availability of resources can play an important role in successful adoption of Six Sigma that can be powerfully integrated other techniques to get optimum benefits out of it (Nonthaleerak and Hendry, 2008). Furthermore, Pantano et al. (2006) proposed the application of Six Sigma in a cluster of small companies so that they can share their resources and achieve the needed level of inputs as possible solution to overcome the difficulties found in the SMEs:
Finding 5. Six Sigma is very much in use within the manufacturing sector but is growing in the service sector. More research is required to understand Six Sigma adoption within the SMEs.
3.6 Enablers of Six Sigma
There is little evidence in the literature to highlight linkage between Six Sigma and organisation culture despite their combinatorial significance in present day manufacturing or service organisations (Davison and Shagana, 2007). However, sound success of it is likely in the event of continuous refinement of culture in organisation (Kwak and Anbari, 2006). Lee-Mortimer (2007) observed a company-wide training to promote Six Sigma as a relevant tactic to combat initial reluctance towards cultural change. He also suggested that reducing the levels in organisational structure may speed up the adoption of Six Sigma culture. Welch (2005) believed that it is necessary to make Six Sigma a leadership tool for transformation that should permeate into all levels of businesses. The effort required is to change the approach to the implementation of Six Sigma projects from merely using a set of tools to the creation of a culture that should be deeply embedded in every employee (Antony, 2004).
Involvement and commitment from top management is the prime enabler in increasing level of a Six Sigma programme implementation (Chung et al., 2008). Furthermore, in order to facilitate the communication within the organisation and to support the implementation process, information technology (IT) and state of the art information systems infrastructure are fundamental. They continually enable integration of complex tasks in obtaining feasible quality improvement solutions in a short time frame (Hsieh et al., 2007). Thanks to an organised and systematic approach, the role of Six Sigma as a “managerial tool” for improving quality and productivity can be extended to a “systemic tool” for quality and process control (Han et al., 2008).
It is important to note that Six Sigma does not provide a quick and easy solution to all types of manufacturing problems and the environment in which it is introduced (Lee-Mortimer, 2006). Furthermore, he also suggested that SME should gradually adopt Six Sigma as it will help to evenly stretch their resources and capabilities to get the most out of them. Regardless the size of the company, McAdam and Laffert (2004) agree that empowerment of people, involvement, motivation, effective communication, reward and recognition system play a critical role in the success of Six Sigma implementation. This can be achievable through a transformational leadership, which is helpful in motivating employees to attain transcendental goals rather than their own short-term interests (Montes and Molina, 2006). This means adapting the strategy definition, although the above-mentioned authors suggest there are few papers in literature regarding the integration of Six Sigma perspective and practices into the strategy formulation process even if it inherently is a concern for a successful Six Sigma initiative.
The linkage between Six Sigma and organisation culture needs to be understood. Successfully enabling these factors, nurturing quality culture amongst workforce and taking concern for the issues expressed above, will shape improvements and increase productivity, thereby making Six Sigma more pervasive and indispensable in both manufacturing and service organisations:
Finding 6. Committed leadership of top management and fully fledged training are crucial to the success of Six Sigma implementation. Blending IT expertise with Six Sigma to propel improvements and plausible significant savings are also important. Human resource functions need good harmonisation with Six Sigma approach leading to a general involvement within the organisation.
3.7 Links to other disciplines
The pressure to remain competitive by providing a high-quality product to satisfy the customer requirements has led to a comprehensive analysis of quality, speed and agility within and outside the company boundaries. Existing literature explicitly identifies higher customer satisfaction as a significant benefit from the integration of lean and Six Sigma concepts (Thomas et al., 2009; Teresko, 2008) but it does not show consensus about how to create such integration. The majority of the papers present the DMAIC approach as a roadmap and suggest to call on lean tools when appropriate to carry out the two kinds of practices in parallel (Thomas et al., 2009; Proudlove et al., 2008; de Koning et al., 2008). In other cases, some authors identified the absence of a systemic methodology to merge the two concepts resulting in the implementation of lean and Six Sigma in sequence (Näslund, 2008; Shah et al., 2008). What is evident and common, however, is that the amalgamation of the two complementary techniques has brought significant benefits to the company performance.
Six Sigma has also been applied by Kumar et al. (2008) in the context of supply chain design. They used DMAIC approach to analyse mitigation of container security risk. Thanks to the Six Sigma process approach orientation, the supply chain can be monitored and improved using the Six Sigma metrics. Those metrics create a common denominator (defect per unit) for the analysis of all the systems on the same scale, from products to processes (Dasgupta, 2003; Kumar et al., 2008).
As previously stated, there is a debate among the authors about the originality of Six Sigma. Six Sigma offers a common metric to align and evaluate the performance of all the functions within the organisation and gives a methodology to translate the TQM philosophy into practices. Six Sigma also keeps the main principles of TQM such as customer focus (identified as CTQ in the “define” phase within DMAIC), employee involvement (green belts and black belts team leaders who lead self-directed work teams are empowered to make changes), continuous improvement (the “control” phase within DMAIC), enlightened leadership (represented by the champion in Six Sigma team) and fact-based decision making (Six Sigma is visibly data oriented) (Green, 2006; Black and Revere, 2006). There are many benefits applying both Six Sigma and TQM in complementary because in fact Six Sigma is the extension to TQM, in which the TQM philosophy is at the core of Six Sigma. As Andersson et al. (2006) put forward, Six Sigma is a structured methodology within the more general framework of TQM and it provides a series of concepts and tools that support the overall principles and aims of TQM.
The literature also demonstrates the link between Six Sigma and Kaizen (continuous improvement) and defines a structure to improve the company performance using the DMAIC steps and making Six Sigma an ongoing effort (Savolainen and Haikonen, 2007; Ehie and Sheu, 2005; Murugappan and Keeny, 2003). In fact, Kaizen tools are major tools in Six Sigma green belt project.
Not widely documented, however, is the relationship between the Six Sigma and the process management. Hammer (2002) recognises the standing alone as major limit of Six Sigma and states that it should be more aligned with the enterprise and part of the process management in order to identify when the Six Sigma approach is not enough and a radical re-engineering of the process is needed. Equally rarely reported is the link between Six Sigma and sustainability. The first authors to study the topic of sustainability in the production phase were Miron and Skarke (1981). The reason for this was possibly because the concept of sustainability within Six Sigma is implicitly contained within the control phase of the DMAIC. Further research might be needed to identify possible benefits driven by Six Sigma in this promising field:
Finding 7. Six Sigma is a complementary approach to lean, an extension to TQM and is suitable to many applications thanks to its process-oriented view, brought together in a structured methodology to increase the system performance and to ensure a continuous improvement culture.
Issue 2. The key areas of connection between Six Sigma and sustainability as well as the integration between Six Sigma and the enterprise process management remain relatively unexplored.
In recent years there has been a lot of interest in the application of Six Sigma principles. Numerous papers have been presented on this subject substantiating the importance of adopting Six Sigma to improve process performance. This research is carried out to identify the latest trends, various approaches, tools and techniques, benefits and combinations of Six Sigma with other concepts by carrying out a systematic, thematic literature review.
Although there is a considerable amount of publication about Six Sigma and therefore a lot of different points of view, it is possible to identify four interpretations of Six Sigma: a set of statistical tools, an operational philosophy of management, a business culture and an analysis methodology that uses the scientific methods, although the streams are not mutually exclusive but instead, overlapping. The main goals of Six Sigma, however, remain unchanged, i.e. improving efficiency, profitability and capability in the process.
There are a large number of tools and techniques within Six Sigma. The variety of tools, however, often causes confusion as to which tools work best for what circumstance of the businesses. A systematic way to guide the selection of these of tools is desirable. Existing literature also traditionally categorises these Six Sigma tools under DMAIC but classification of tools under other alternative approaches such as DFSS, DCOV or DMADV is lacking. Possible explanation of this is that all these DFSS tools are custom selected for a particular R&D process, industry and use, so a fixed formulation is not possible beyond a broad categorisation (Watson, 2005).
Another issue, as mentioned before, is to clarify the use of the statistical tools and to understand how the simulation can help in the proactive analysis of the systems. Simulation techniques have been identified as one of the promising ones.
The main enabler for Six Sigma implementation is the top management commitment that can promote an effective company-wide training to let all the employees be involved in the project.
The initial methodology of Six Sigma was focused on process improvement and accordingly DMAIC approach was universally adopted, but as time progressed, the need of implementing Six Sigma at design stage of product (or process) was felt crucial and hence the concept of DFSS was developed. Several slightly different variations of the aforementioned approaches are available in the literature.
Despite the increased number of papers discussing the adoption of Six Sigma in the service sector in the last few years, the detailed implementation in SMEs was not widely reported in the academic literature, with the exception of, e.g. Antony et al. (2005a) and Nonthaleerak and Hendry (2008).
The literature also supports the view that by adopting Six Sigma the variability in a process will be reduced. In addition to the direct savings which are achieved by improved quality and reduced scrap, the organisation can also be benefited from the indirect savings such as in lower rework cost, minimum product recalls, low warranty liabilities, higher customer satisfaction and brand loyalty.
These findings support the view that despite Six Sigma is considered as a fully developed methodology, further research is needed to establish a more systematic approach to help companies, especially SMEs, embark on Six Sigma projects. Although the general approach is quite well known and largely applied in large manufacturing organisations, further work is required to investigate implementation of Six Sigma in the service sector as well as in smaller companies.
This paper has extended the work of Brady and Allen (2006). The findings and issues have provided new insights to take Six Sigma to the next level. This work also contributes the theoretical platform enabling deeper analyses to be carried out on the highlighted fields. As Six Sigma continues to develop and evolve, this type of work should also carry on.
As for the future work, the key findings and issues arising from the evidence gained in the literature need to be further validated, in particular, confirmation of the possible link between Six Sigma and other concepts such as sustainability and the emerging business model of product service systems (Baines et al., 2009). How Six Sigma can be used to facilitate manufacturing organisations to shift from selling product only to selling integrated product and services, for example, is yet to be explored. The authors are mindful that Six Sigma principles and theories were not developed solely in the academic journals, but instead progressed out of the practitioners. The role of academics in this respect is to underpin these developments with a theoretical basis.
Figure 1Number of articles and their authorship
Figure 2Percentage of articles focused on manufacturing and services
Table IKeywords search results
Aghili, S. (2009), "A Six Sigma approach to internal audits", Strategic Finance, Vol. 90 No.8, pp.38-43.
Al-Mishari, S.T., Suliman, S. (2008), "Integrating Six-Sigma with other reliability improvement methods in equipment reliability and maintenance applications", Journal of Quality in Maintenance Engineering, Vol. 14 No.1, pp.59-70.
Anand, R.B., Shukla, S.K., Ghorpade, A., Tiwari, M.K., Shankar, R. (2007), "Six Sigma-based approach to optimise deep drawing operation variables", International Journal of Production Research, Vol. 45 No.10, pp.2365-85.
Andersson, R., Eriksson, H., Torstensson, H. (2006), "Similarities and differences between TQM, Six Sigma and lean", TQM Magazine, Vol. 18 No.3, pp.282-96.
Antony, J. (2004), "Some pros and cons of Six Sigma: an academic perspective", TQM Magazine, Vol. 16 No.4, pp.303-6.
Antony, J. (2007), "Is Six Sigma a management fad or fact?", Assembly Automation, Vol. 27 No.1, pp.17-19.
Antony, J., Kumar, M., Madu, C.N. (2005a), "Six Sigma in small and medium sized UK manufacturing enterprises", International Journal of Quality & Reliability Management, Vol. 22 No.8, pp.860-74.
Antony, J., Kumar, M., Tiwari, M.K. (2005b), "An application of Six Sigma methodology to reduce the engine-overheating problem in an automotive company", Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 219 No.8, pp.633-46.
Arnheiter, E.D., Maleyeff, J. (2005), "The integration of lean management and Six Sigma", TQM Magazine, Vol. 17 No.1, pp.5-18.
Baines, T.S., Lightfoot, H.W., Benedettini, O., Kay, J.M. (2009), "The servitization of manufacturing: a review of literature and reflection on future challenges", Journal of Manufacturing Technology Management, Vol. 20 No.5, pp.547-67.
Banuelas, R., Antony, J. (2004), "Six Sigma or design for Six Sigma", TQM Magazine, Vol. 16 No.4, pp.250-63.
Black, K., Revere, L. (2006), "Six Sigma arises from the ashes of TQM with a twist", International Journal of Health Care Quality Assurance, Vol. 19 No.3, pp.259-66.
Brady, J.E., Allen, T.T. (2006), "Six Sigma literature: a review and agenda for future research", Quality & Reliability Engineering International, Vol. 22 pp.335-67.
Breyfogle, F.W. III (2008), "Better fostering innovation: 9 steps that improve lean Six Sigma", Business Performance Management Magazine, Vol. 6 No.3, pp.16-20.
Bunce, M.M., Wang, L., Bidanda, B. (2008), "Leveraging Six Sigma with industrial engineering tools ins crateless retort production", International Journal of Production Research, Vol. 46 No.23, pp.6701-19.
Chakrabarty, A., Tan, K.C. (2007), "The current state of Six Sigma application in services", Managing Service Quality, Vol. 17 No.2, pp.194-208.
Chung, Y.C., Hsu, Y.W., Tsai, C.H. (2008), "An empirical study on the correlation between critical DFSS success factors, DFSS implementation activity levels and business competitive advantages in Taiwan's high-tech manufacturers", Total Quality Management, Vol. 19 No.6, pp.595-607.
Coleman, S. (2008), "Six Sigma: an opportunity for statistics and for statisticians", Significance, Vol. 5 No.2, pp.94-6.
Dasgupta, T. (2003), "Using the Six-Sigma metric to measure and improve the performance of a supply chain", Total Quality Management & Business Excellence, Vol. 14 No.3, pp.355-66.
Davison, L., Shaghana, K. (2007), "The link between Six Sigma and quality culture: an empirical study", Total Quality Management, Vol. 18 No.3, pp.249-65.
de Koning, H., de Mast, J. (2006), "A rational reconstruction of Six-Sigma's breakthrough cookbook", International Journal of Quality & Reliability Management, Vol. 23 No.7, pp.766-87.
de Koning, H., de Mast, J., Does, R.J.M.M., Vermaat, T., Simons, S. (2008), "Generic lean Six Sigma project definitions in financial services", Quality Management Journal, Vol. 15 No.4, pp.32-45.
Edgeman, R.L., Dugan, J.P. (2008), "Six Sigma from products to pollution to people", Total Quality Management, Vol. 19 No.1-2, pp.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, Vol. 16 No.5, pp.542-53.
Ferrin, D., Miller, M., Muthler, D. (2005), "Lean sigma and simulation, so what's the correlation? V2", Proceedings of the 2005 Winter Simulation Conference, Orlando, FL, 4-7 December, pp.2011-15.
Furterer, S., Elshennawy, A.K. (2005), "Implementation of TQM and lean Six Sigma tools in local government: a framework and a case study", Total Quality Management & Business Excellence, Vol. 16 No.10, pp.1179-91.
Gladwin, B. (2003), "Six Sigma & simulation", Promodel White Paper, .
Goh, T.N., Xie, M. (2004), "Improving on the Six Sigma paradigm", TQM Magazine, Vol. 16 No.4, pp.235-40.
Gowen, C.R. III, Stock, G.N., McFadden, K.L. (2008), "Simultaneous implementation of Six Sigma and knowledge management in hospitals", International Journal of Production Research, Vol. 46 No.23, pp.6781-95.
Green, F.B. (2006), "Six-Sigma and the revival of TQM", Total Quality Management & Business Excellence, Vol. 17 No.10, pp.1281-6.
Hagemeyer, C., Gershenson, J.K., Johnson, D.M. (2006), "Classification and application of problem solving quality tools", TQM Magazine, Vol. 18 No.5, pp.455-83.
Haikonen, A., Savolainen, T., Järvinen, P. (2004), "Exploring Six Sigma and CI capability development: preliminary case study findings on management role", Journal of Manufacturing Technology Management, Vol. 15 No.4, pp.369-78.
Halliday, S. (2005), "Application of tools in Six Sigma", available at: www.wdpc.co.uk/articles/tools6sig.pdf (accessed 25 November 2009), .
Hammer, M. (2002), "Process management and the future of Six Sigma", MIT Sloan Management Review, Vol. 43 No.2, pp.26-32.
Han, H.S., Chae, M.J., Im, K.S., Ryu, H.D. (2008), "Six Sigma-based approach to improve performance in construction operations", Journal of Management in Engineering, Vol. 24 No.1, pp.21-31.
Hensley, R.L., Dobie, K. (2005), "Assessing readiness for Six Sigma in a service setting", Managing Service Quality, Vol. 15 No.1, pp.82-101.
Hong, K., Nagarajah, R., Iovenitti, P., Dunn, M. (2007), "A sociotechnical approach to achieve zero defect manufacturing of complex manual assemblies", Human Factors and Ergonomics in Manufacturing, Vol. 17 No.2, pp.137-48.
Hsieh, C.T., Lin, B., Manduca, B. (2007), "Information technology and Six Sigma implementation", Journal of Computer Information Systems, Vol. 47 No.4, pp.1-10.
Johnston, A.B., Maguire, L.P., McGinnity, T.M. (2008), "Disentangling causal relationships of a manufacturing process using genetic algorithms and Six-Sigma techniques", International Journal of Production Research, Vol. 46 No.22, pp.6251-68.
Kumar, M., Antony, J., Antony, F.J., Madu, C.N. (2006), "Winning customer loyalty in an automotive company through Six Sigma: a case study", Quality Reliability Engineering International, Vol. 23 pp.849-66.
Kumar, M., Antony, J., Madu, C.N., Montgomery, D.C., Park, S.H. (2008), "Common myths of Six Sigma demystified", International Journal of Quality & Reliability Management, Vol. 25 No.8, pp.878-95.
Kumar, S., Bauer, K.F. (2010), "Exploring the use of lean thinking and Six Sigma in public housing authorities", Quality Management Journal, Vol. 17 No.1, .
Kumar, S., Jensen, H., Menge, H. (2008), "Analyzing mitigation of container security risk using Six Sigma DMAIC approach in supply chain design", Transportation Journal, Vol. 47 No.2, pp.54-67.
Kumar, U.D., Nowicki, D., Ramirez-Marquez, J.R., Verma, D. (2007), "On the optimal selection of process alternatives in a Six Sigma implementation", International Journal of Production Economics, Vol. 111 pp.456-67.
Kwak, Y.H., Anbari, F.T. (2006), "Benefits, obstacles and future of Six Sigma approach", Technovation, Vol. 26 No.5-6, pp.708-15.
Lee-Mortimer, A. (2006), "Six Sigma: a vita improvement approach when applied to the right problems, in the right environment", Assembly Automation, Vol. 26 No.1, pp.10-17.
Lee-Mortimer, A. (2007), "Leading UK manufacturer probes the potential of Six Sigma", Assembly Automation, Vol. 27 No.4, pp.302-8.
Lin, L.C., Li, T.S., Kiang, J.P. (2008), "A continual improvement framework with integration of CMMI and Six-Sigma model for auto industry", Quality & Reliability Engineering International, Vol. 25 No.5, pp.551-69.
McAdam, R., Evans, A. (2004), "Challenges to Six Sigma in a high technology mass manufacturing environments", Total Quality Management, Vol. 15 No.5-6, pp.699-706.
McAdam, R., Laffert, B. (2004), "A multilevel case study critique of Six Sigma: statistical control or strategic change?", International Journal of Operations & Production Management, Vol. 24 No.5-6, pp.530-49.
McCarthy, B., Stauffer, R. (2001), "Enhancing Six Sigma through simulation with iGrafx process for Six Sigma", Proceedings of the 2001 Winter Simulation Conference, 2, 9-12 December 2001, Arlington, VA, pp.1241-7.
Maciel Junior, H., Batista Turrioni, J., Cesar Rosati, A., Garcia Neto, D., Kenji Goto, F., Fujioka Mologni, J., Machado Fernandes, M. (2008), "Application of design for Six Sigma (DFSS) on an automotive technology development process", SAE International, Warrendale, PA, SAE Technical paper series, .
Mader, D.P. (2006), "Deploying the ‘D’ in DFSS", Quality Progress, Vol. 39 No.7, pp.73-4.
Mahanti, R., Antony, J. (2005), "Confluence of Six Sigma, simulation and software development", Managerial Auditing Journal, Vol. 20 No.7, pp.739-62.
Markarian, J. (2004), "What is Six Sigma?", Reinforced Plastics, No.July-August, pp.46-9.
Miron, J.R., Skarke, P. (1981), "Non-price information and price sustainability in the Koopmanns-Beckmann problem", Journal of Regional Science, Vol. 21 No.1, pp.117-22.
Mitra, A. (2004), "Six Sigma education: a critical role for academia", TQM magazine, Vol. 16 No.4, pp.293-302.
Montes, F.J.L., Molina, L.M. (2006), "Six Sigma and management theory: processes, content and effectiveness", Total Quality Management, Vol. 17 No.4, pp.485-506.
Morgan, J., Brennig, M.J. (2006), "Six Sigma and the future of quality", Management Services, Vol. 50 No.2, pp.46-7.
Murugappan, M., Keeny, G. (2003), "Blending CMM and Six Sigma to meet business goals", IEEE Software, Vol. 20 No.2, pp.42-8.
Näslund, D. (2008), "Lean, Six Sigma and lean sigma: fads or real process improvement methods?", Business Process Management Journal, Vol. 14 No.3, pp.269-87.
Nonthaleerak, P., Hendry, L. (2008), "Exploring the Six Sigma phenomenon using multiple case study evidence", International Journal of Operations & Production Management, Vol. 28 No.3, pp.279-303.
Oke, S.A. (2007), "Six Sigma: a literature review", South African Journal of Industrial Engineering, Vol. 18 No.2, pp.109-29.
Pantano, V., Kane, P.O., Smith, K. (2006), "Cluster-based Six Sigma deployment in small and medium sized enterprises", Management of Innovation and Technology, Vol. 2 pp.788-92.
Patel, S.C., Zu, X. (2009), "E-government application development using the Six Sigma approach", Electronic Government: an International Journal, Vol. 6 No.3, pp.295-306.
Pheng, L.S., Hui, M.S. (2004), "Implementing and applying Six Sigma in construction", Journal of Construction Engineering and Management, Vol. 130 No.4, pp.482-9.
Proudlove, N., Moxham, C., Boaden, R. (2008), "Lessons for lean in healthcare from using Six Sigma in the NHS", Public Money & Management, Vol. 28 No.1, pp.27-34.
Raja, A. (2006), "Simple tools for complex systems", Quality Progress, Vol. 39 No.6, pp.40-4.
Ranch, H. (2006), "Xerox find the right tool for tracking continuous improvement", Manufacturing Business Technology, Vol. 24 No.2, pp.42-5.
Savolainen, T., Haikonen, A. (2007), "Dynamics of organizational learning and continuous improvement in Six Sigma implementation", TQM Magazine, Vol. 19 No.1, pp.6-17.
Schroeder, R.G., Linderman, K., Liedtke, C., Choo, A.S. (2008), "Six Sigma: definition and underlying theory", Journal of operations management, Vol. 26 pp.536-54.
Sehwail, L., DeYong, C. (2003), "Six Sigma in health care", Leadership in Health Services, Vol. 16 No.4, pp.1-5.
Senapati, N.R. (2004), "Quality and reliability corner: Six Sigma: myths and realities", International Journal of Quality & Reliability Management, Vol. 21 No.6/7, pp.683-90.
Shah, R., Chandrasekaran, A., Linderman, K. (2008), "In pursuit of implementation patterns: the context of lean and Six Sigma", International Journal of Production Research, Vol. 46 No.23, pp.6679-99.
Teresko, J. (2008), "How to organize for lean/Six Sigma", Industry Week, Vol. 257 No.11, pp.38-41.
Thawani, S. (2004), "Six Sigma – strategy for organizational excellence", Total Quality Management, Vol. 15 No.5-6, pp.655-64.
Thawesaengskulthai, N., Tannock, J.D.T. (2008), "A decision aid for selecting improvement methodologies", International Journal of Production Research, Vol. 46 No.23, pp.6721-37.
Thomas, A., Barton, R., Chuke-Okafor, C. (2009), "Applying lean Six Sigma in a small engineering company – a model for change", Journal of Manufacturing Technology Management, Vol. 20 No.1, pp.113-29.
van den Heuvel, J., Does, R.J.M.M., Verver, J.P.S. (2005), "Six Sigma in healthcare: lessons learned from a hospital", International Journal of Six Sigma and Competitive Advantage, Vol. 1 No.4, pp.380-8.
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, Vol. 46 No.23, pp.6739-58.
Ward, S.W., Poling, S.R., Clipp, P. (2008), "Selecting successful Six Sigma projects", Quality, Vol. 47 No.10, pp.50-1.
Watson, G.H. (2005), Design for Six Sigma: Innovation for Enhanced Competitiveness, Goal/QPC, Salem, NH, .
Watson, G.H., deYong, C.F. (2010), "Design for Six Sigma: caveat emptor", International Journal of Lean Six Sigma, Vol. 1 No.1, pp.66-84.
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Welch, J. (2005), "Six Sigma leaders", Quality, Vol. 44 No.3, pp.80.
William, S. (2009), "The lean toolkit, Part I", CiruiTree, Vol. 22 No.2, pp.36.
Yang, H.M., Choi, B.S., Park, H.J., Suh, M.S., Chae, B. (2007), "Supply chain management Six Sigma: a management innovation methodology at the Samsung Group", Supply Chain Management: An International Journal, Vol. 12 No.2, pp.88-95.
About the authors
B. Tjahjono is a Lecturer in Manufacturing Systems Engineering and the Director of the Manufacturing Masters Programme at Cranfield University. He is currently leading a research team in the area of contemporary simulation modelling techniques and applications. He has been working closely with global companies such as Ford and Rolls-Royce on a number of industrial research projects involving analysis and design of manufacturing systems and their supply chain.
P. Ball is a Senior Lecturer in Manufacturing Operations. Starting from a base in manufacturing simulation Peter's work has expanded to include production planning and control, manufacturing supply design, supply chain design and e-business simulation and modelling. Research projects include the development of business collaboration models, business process outsourcing and development of e-business modelling as well as work further afield in business process innovation and brand value performance measurement.
V.I. Vitanov is a Professor of Design Manufacture and Management in the School of Engineering and Computer Sciences, Durham University and Visiting Professor in the School of Applied Sciences, Cranfield University, UK. He has over 25 years of experience in four closely related areas, product design and technology optimisation, production and operation management, simulation of discrete event dynamic systems, systems engineering and autonomous robotics with over 90 publications. He has long-term relationship with international companies such as BAE Systems, EATON Corporation, Rolls Royce, BMW, Frictec, etc.
C. Scorzafave, J. Nogueira, J. Calleja, M. Minguet, L. Narasimha, A. Rivas, A. Srivastava, S. Srivastava and A. Yadav are postgraduate students at the Manufacturing Department, Cranfield University, and the team members of a research project funded by Ford Motor Company to explore the application of Six Sigma in the design of engine assembly facilities.