1. Six sigma is a compilation of tools as well as strategies for the purpose of process improvement, which was initially innovated by Motorola in the year 1985. This model attempts to develop the quality of the process outputs through identification and removal of the causes of the defects and the minimisation of variation in manufacturing as well as the business processes (Lakhiani et al. 2014). This model makes use of various methods of quality management which includes the following:
Every Six Sigma model related project follows a particular sequence and strategies for cost reduction and parallely increment of profit. By virtue of manufacturing through this model it can be expected that 99.99966% products would be defect free.
There are a lot of benefits of using the QFD matrix. The primary feature of is that this matrix is entirely based on addressing the requirements of the customers. The fact that it is a customer driven and not a technology driven process, gives the companies using the model, an added advantage to create customer specific solutions. With the application of the QFD, the final criteria of the product are already set and the implementation team works towards incorporating the technical specifications of the design based on the final layout of the model of product improvisation for a new launch (Mason, Nicolay and Darzi 2015). Finally, QFD also helps in the process of production planning that helps in setting up process control as also maintenance plans. The application of the QFD also improves the efficiency of production. Since the concept stage, this model dictates the designing and manufacturing standards for the launch of the new products. This helps the production team to address any issues at an stage at the early production phase and as an impact, there is the maximum proximity for the final product to be flaw free.
Lastly this model also helps in fostering teamwork in any department of the company. Under the discourse of this model, the marketing as well as the sales team works together and conducts an elaborate market research to find out the specific customer’s expectations. This in turn also helps the engineering department to improvise the technical specifications properly since an early phase (Mason, Nicolay and Darzi 2015). This is how this model helps all the departments to works in unison to focus on same goal.
There are four phases of a QFD matrix. The first stage is product definition. This phase advents with the formulation of the VOC and hereby the model helps in the translation of the customers’ demands in to the product specifications (Cherrafi et al. 2016). This phase might also involve competitive analysis for effective evaluation of the fulfilment of the customers’ needs and demands.
The next phase is product development. This phase involves the identification of the critical parts as well as the assemblies. The specifications of the product are cascaded down and translated towards assembly of the key parts.
The next phase is process development. As informed by Akpolat (2017), this phase involves the manufacture as well as the assembly processes based on the prior selected product as well as component specifications. In this phase, alongside the development of the product flow the critical process characters are also identified.
The last process is “Process Quality Control”. In advance to the launch of the product, the process parameters are well defined alongside development of the correct process controls. On top of that inspection as well as test specifications are also performed (Albliwi et al. 2014). Full production starts after the execution of the process capability at the time of the pilot build.
The critical steps incorporated in the benchmarking planning process are as follows:
Affinity diagram is an instrument which works towards gathering large quantity of language data which includes ideas, information as well as issues. Then, as Albliwi, Antony and Lim (2015), states, the gathered information is manipulated and accommodated in to groupings, based up on their original relationships. This affinity process is very often used for the grouping of ideas which are being generated by virtue of brainstorming.
The Kano Model is purposefully created for creating visual model of the customer’s provided characteristics which is plotted against the satisfaction level which is delivered by every characteristic. This model can be viewed as a tool for product development as well as customer satisfaction, specially designed for categorisation of the preferences of the customers. This tool is implemented after the data collection during the “Voice of customer” phase. The VOC is an IT term used for describing the in depth procedure
This is a formal technique which is chiefly implemented in those cases where the probable action discourses are competing for attention. The entity designated for problem solving makes an estimation of the benefits that are delivered through each of the actions (Antony 2014). Then the number of the most impactful action discourses are selected which would deliver an all over benefit which is most proximate to the maximum benefit.
Brainstorming can be perceived as a technique that requires group activity which involves efforts required to find one solution to the specific problem through collection of one list of ideas that are spontaneously contributed to, by the members. Brainstorming can also be described as a kind of situation that is that is created by a group that generates innovative ideas as well as solutions (Kovach et al. 2017). All ideas are being noted down during the brainstorming session and at the end of the session none of the rejected ideas are criticised.
A cause and effect framework which is known as Fish Bone diagram can be helpful in brainstorming for identification of plausible causes against a problem and sorting of ideas in to prominent categories.
This is a visual representation to the sequence related to steps as well as decisions for performing one process. Every step within the sequence in recorded within a shape of a diagram.
This is a highly systematic methodology for analysis of failures. The framework have been developed by the reliability engineers for studying the problems arising from the malfunctions related to the military systems (Kovach et al. 2017).
This is a systematic method required for the determination of the relationship involving factors that can affect one process as also the output that comes as a result of the implementation of the process. Otherwise also, this process is used for finding the cause and effect relationship (Timans et al. 2016). This process is also required for managing process inputs for the optimisation of the output.
The fifth or the last step is useful for the sustenance of the improvement. Another important accomplishment of the control phase is the process to maintain the gains. The team, during this phase, focuses on creation of a monitoring plan so that the measurement of the success of the updated process can be continued and parallely one response plan can be also framed, if there is in case, a performance drop located. After the development of the blue print, the process owner have all liabilities of ongoing maintenance.
For effective lean process improvement, every department in the organisation needs to accept and also undergo the process of change. In case if this do not happen, the companies are actually undertaking the risks of enabling selective workgroups to optimise their performance and thereby sub optimise another team’s performance (Marzagão and Carvalho 2016). Thus, the performance of the whole framework is impacted. The primary target of Lean Process improvement is to make the teams enabled to find systematic ways for delivering value to the customers. This is done through the provision of systematic as well as scientific approach to make continuous improvement, a daily component.
Two most important tools for lean process improvement are Kanban as well as WIP limits. The Kanban is a visual workflow that can enable entities to manage work by means of shared understanding of the process. The WIP is another technique of lean management. These limits are fixed constraints which he teams place by themselves for improving throughout. ?
One importance of value stream mapping is identification of processes which does not provide value. This mapping framework documents the current position of the value stream and the future state of value stream, as well as defining the gapping between the 2.
DFSS is another approach towards new product and/or process development. DFSS is currently used for the completion of the redesigning of one product as well as process. The implementation process of DFSS varies on the basis of the business making company that is implementing the process. Some examples of the process are DCCDI, IDOV and so on. The basic plan against using DFSS is designing products and/or processes with the aim of reducing defects or variations.
DFSS methodology can redesign one IT solution which have the potential to effectively communicate information among the layers within supply chain concerning movement of the materials through inland tank barges.
The critical factors for the successful implementation of Six-Sigma are as follows:
Again, the basic challenges to the implementation of the Six Sigma are as follows:
The supply chain of an organisation should be agile as well as promptly responsive towards the customers’ changing needs. The companies attuned to the alternating demands of the customers have already accomplished one vital step in the creation of supply chain that is essential for the fulfilment of the needs (Gupta et al. 2018). In the define phase, Six Sigma needs the organisations to evaluate their progress so that the customers remain critical towards quality.
Supply chain that is implemented with high rate of errors need implementation of lean six sigma. The lean technique of Poka Yoke can be beneficial in this context. This is actually a mistake identification software that prevents making of mistake by complying the user to do the task correctly. For any logistics company, Six Sigma presents three different strategies. It is meant for improvement of processes, redesigning the process which are outdated and irrelevant. This is of great help towards the logistics regarding ongoing process management.
One common issue regarding logistics arises while dealing with shipment errors. These issues are not reported by customers after accepting the delivery and are not also realised by the organisation after the accomplishment of the delivery. One incorrect shipment each month is also counted as unacceptable in the perception of that process, particularly then there is a proper reason why the erroneous persist to happen. Implementation of end to end lean six sigma projects helps large logistics as well as shipping companies to save wealth and increase the process of utilisation of pickup trucks by a large percentage in spans of less than a year.
This is a model of process reference endorsed by the Council of Supply Chain and is accepted as the standard cross country diagnostic tool in case of supply chain management. This model describes the process related to business activities which are associated with customer demand satisfaction. The activities include planning, resourcing, delivering, returning and enabling. The usage of this model incorporates analysis of the current state of the processes and goals of the company quantification of the operational performance and comparison of company’s performance against benchmark data. SCOR model incorporates a set of parameters for evaluating performance of the supply chain.
SCOR consists of various hierarchical levels. These includes evaluation of strategic objectives as well as goals in relation to competitive analysis of supply chain. Value chain mapping involving the major processes of workflows and at the minimum level, analysing work tasks, metrics as well as procedures. However, the SCOR model is beneficial in that it is customisable for fitting in specific supply chain of any of the organisations. However, major processes of workflows are standardised including the basic control elements that are based up on combined knowledge of many exponents of the industry.
Creation of supply chain processes or implementation of model helps an organisation to detect as well as eliminate the process variation. The reason is that variation from well proclaimed standard is easily detectable. Analysis and implementation of the six sigma helps in their elimination. For example, lean methods can be easily applied for simplification, standardisation as well as mistaking proof process workflows before migration to the SCOR model.
Reference List
Akpolat, H., 2017. Six sigma in transactional and service environments. Routledge.
Albliwi, S., Antony, J., Abdul Halim Lim, S. and van der Wiele, T., 2014. Critical failure factors of Lean Six Sigma: a systematic literature review. International Journal of Quality & Reliability Management, 31(9), pp.1012-1030.
Albliwi, S.A., Antony, J. and Lim, S.A.H., 2015. A systematic review of Lean Six Sigma for the manufacturing industry. Business Process Management Journal, 21(3), pp.665-691.
Alsyouf, I., Kumar, U., Al-Ashi, L. and Al-Hammadi, M., 2018. Improving baggage flow in the baggage handling system at a UAE-based airline using lean Six Sigma tools. Quality Engineering, pp.1-21.
Antony, J., 2014. Readiness factors for the Lean Six Sigma journey in the higher education sector. International Journal of Productivity and Performance Management, 63(2), pp.257-264.
Antony, J., 2015. Six-sigma for improving Top-Box Customer Satisfaction score for a banking call centre. Production Planning and Control, 26(16), pp.1291-1305.
Borse, G.U. and Attarde, P.M., 2016. Application of six sigma technique for commercial construction project-A review. International Research Journal of Engineering and Technology, 3(6), pp.2323-2328.
Cherrafi, A., Elfezazi, S., Chiarini, A., Mokhlis, A. and Benhida, K., 2016. The integration of lean manufacturing, Six Sigma and sustainability: A literature review and future research directions for developing a specific model. Journal of Cleaner Production, 139, pp.828-846.
Drohomeretski, E., Gouvea da Costa, S.E., Pinheiro de Lima, E. and Garbuio, P.A.D.R., 2014. Lean, Six Sigma and Lean Six Sigma: an analysis based on operations strategy. International Journal of Production Research, 52(3), pp.804-824.
Ellis, B.D. and Walton, S., 2017. Implementation of Six Sigma training and certification at the university level.
Furterer, S.L., 2016. Lean Six Sigma in service: applications and case studies. CRC press.
Gupta, S.K., Antony, J., Lacher, F. and Douglas, J., 2018. Lean Six Sigma for reducing student dropouts in higher education–an exploratory study. Total Quality Management & Business Excellence, pp.1-16.
Jacobs, B.W., Swink, M. and Linderman, K., 2015. Performance effects of early and late Six Sigma adoptions. Journal of Operations Management, 36, pp.244-257.
Kovach, J.V., Curiel, V., Franklin York, A., Bogard, S. and Revere, L., 2017. Enhancing information sharing in family drug courts: A Lean Six Sigma case study. Juvenile and Family Court Journal, 68(3), pp.27-41.
Lakhiani, C., Moroni, E., Evans, K.K., Steinberg, J., Kim, P.J. and Attinger, C.E., 2017. Utility of Six Sigma Methodology for Improving Quality and Safety in a Large Surgical Service: A Resident Driven Protocol. Plastic and Reconstructive Surgery Global Open, 5(9 Suppl).
Marzagão, D.S.L. and Carvalho, M.M., 2016. Critical success factors for Six Sigma projects. International Journal of Project Management, 34(8), pp.1505-1518.
Mason, S.E., Nicolay, C.R. and Darzi, A., 2015. The use of Lean and Six Sigma methodologies in surgery: a systematic review. The Surgeon, 13(2), pp.91-100.
Timans, W., Ahaus, K., van Solingen, R., Kumar, M. and Antony, J., 2016. Implementation of continuous improvement based on Lean Six Sigma in small-and medium-sized enterprises. Total Quality Management & Business Excellence, 27(3-4), pp.309-324.
Yaduvanshi, D. and Sharma, A., 2017. Lean Six Sigma in Health Operations: Challenges and Opportunities—‘Nirvana for Operational Efficiency in Hospitals in a Resource Limited Settings’. Journal of Health Management, 19(2), pp.203-213.
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