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The problems faced by the SSI might be of different, but the methodology followed helps all other SSI to implement SS, being under their limitations.In this paper, we present an iterative scheme integrating simulation with an optimization model, for solving complex problems, viz., job shop scheduling. But being under constraint, study has helped to increase the productivity of the organization.
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Further, due to the limited resources such as time, capital investment, and level of adaptability all the factors which would improve the productivity could not be tackled.
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But, lessons learned and managerial implications are applicable to similar industries and projects. The current project is based on the single case study thus results cannot be generalized. Rework of the leaf plate assembly which was a major concern of industry has been reduced. Implementation of the SS methodology has resulted in increased productivity in the organization. MINITAB statistical software is used to interpret the results.
![anylogic tutorials job shop anylogic tutorials job shop](https://anylogic.help/tutorials/bank-office/images/run_4_2.png)
Further, DMAIC (Definition-Measure-Analysis-Improve-Control) approach is used to effectively deploy SS strategy. The article presents a case study, conducted to increase the productivity by implementing Six Sigma (SS) methodology in a traditional Small Scale Industry (SSI) with very low capital investment and minimum changes to the existing technology. I do assure that this research study will provide opportunities to the organizations for the better implementation of six sigma projects. Time and commitment both are required and compulsory to bring change in cultural before they are strongly implanted into the organization. The valuable principles and practices of Six Sigma will do well by continuously refining the organizational culture. Electricity Problem, Shortage of Material, Quality Issues, Machine Fault and Reactive Maintenance. This study also highlighted the five critical problems (reasons) of Downtime, which are i.e. The results of this study show that sigma value has improved from 2.79 Sigma to 2.85 Sigma. The tools and techniques used during the analysis are Process Mapping (SIPOC Diagram), Process Flow Chart, Process Capability Analysis, Histogram, Pareto Chart, Pie Chart, Cause and Effect Diagram, Brainstorming, Affinity Diagram and ANOVA. This case study based research deals with application of DMAIC (Define, Measure, Analyze, Improve and Control) methodology of Six Sigma to reduce the machine downtime for process improvement. In the last three decades, it helped several companies to enhance the capability of their processes and to increase the level of quality of their product or service. Six Sigma is a quality improvement approach that aims to reduce the number of defects up to 3.4 parts per million. This is an era of quality management and quality is a parameter for the selection of a product or service because the customer wants a defects free product or service. This paper also shows the fundamental relationship between six sigma and anylogic simulation in manufacturing line on effectively way. Here on the six sigma method implemented by DMAIC through over an industry on effectively way however it to identify the problem causing approaches in manufacturing organization alongside anylogic simulation using discrete event simulation (DE) and agent based simulation (AB). The idea of this paper is to implementing combination of both six sigma and anylogic simulation in real case manufacturing industry for reduction processing time, improve processes and improve productivity using statistical data analysis and embedding for continues improvement an organization in practice. As we know six sigma method have been developed as become improved the capability of process performance and reduce wastage. Many types of manufacturing industries uses the different types of simulation techniques with different methods either integrated or individual to optimize their performance and increase production capacity.