Parikalpana: KIIT Journal of Management

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Manufacturing Excellence Model To Solve Operational Risks Due To Product Demand Variations


Affiliations
1 Sandip University, Nashik, India
 

The dynamic product demand impacts the manufacturing supply cycle by creating some operational risks like high inventories, excess manpower, and underutilization of machines, etc. Business firms or companies get impacted financially due to the dynamic product demand with issues like rising finish goods, raw material, and in-process stocks or inventories, inefficient usage of resources like machines, water, and people, and excess or less manpower or job cuts.

We studied the lean manufacturing principle in a literature survey to understand the concept of the manufacturing excellence at the product manufacturing and its deployment to solve the above-listed issues due to product demand variations. Further, in research methodology, we considered the independent variable as dynamic product demand and the dependent variable as operational risks like high inventories, excess manpower, and underutilization of machines. We plotted the value stream map for the selected product manufacturing with daily demand 25 and 40 numbers to understand the operation risks that occur after changing the demands.

We proposed consolidated manufacturing excellence models for solving the operational risks and after deployment of them; we again plotted the value stream map for the selected product manufacturing with daily demand 25 and 40 numbers. We got gain of in the case of the daily 25 demand, total lead time reduced from 14.6 to 7.82 days that is 46.44% for in-house product manufacturing and in the case of the daily 40 demand, total lead time reduced from 26.18 to 15.18 days that is 42.01%. Total lead time in both cases is reduced by +40% that helped product manufacturing.

We conclude this research study as our manufacturing excellence models are successful in delivering the expected results at our selected product manufacturing.


Keywords

VSM, Lean, Manufacturing Excellence Model, Inventory, Operational Risks.
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  • D. Rizzardo and R. Brooks. (2003). Understanding Lean Manufacturing, Maryland Technology Enterprise Institute.

  • Hoyle, David (2007), Quality Management Essentials, Oxford, United Kingdom: Butterworth-Heinemann, p. 200, ISBN 9780750667869.

  • Industry forum, (2020). Manufacturing Operations is where people, and produce goods for sale. Retrieved from, https://www.industryforum.co.uk/consultancy/manufacturing-operations/#:~:text=ManufacturingOperationsis wherepeople,andproducegoodsforsale.

  • Jamie R. Friddle. (2020). Heijunka the art of levelling production. Retrieved from https://www.isixsigma.com/methodology/lean-methodology/heijunka-the-art-of-leveling-production/.

  • Kanbanize. (2020). The built in quality management of continuous improvement. Retrieved from https://kanbanize.com/lean-management/improvement/continuous-quality-improvement.

  • Kenge, Rohit. & Khan, Zafar. (2020). THE RECESSION, ITS IMPACT AND INDIA’S RESPONSE. World Affairs. 24(3). 98-109.

  • Kenge, Rohit & Khan, Zafar. (2020). A CONCEPTUAL STUDY OF THE SUPPLY CHAIN MANAGEMENT 4.0 IMPLEMENTATION PROCESS. GSTF Journal of Engineering Technology. 10(2). 12-16. 10.46360/cosmos.

  • Mika, Geoffrey L. (1999). Kaizen Event Implementation Manual.

  • Neil Kokemuller, (2020). Manufacturing operations management.Retrieved from, https://smallbusiness.chron.com/manufacturing-operations-management-69293.html.

  • Padovano, Antonio; Longo, Francesco; Nicoletti, Letizia; Mirabelli, Giovanni (January 1, 2018). “A Digital Twin based Service Oriented Application for a 4.0 Knowledge Navigation in the Smart Factory”. IFAC-PapersOnLine. 16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018. 51 (11): PP 631–636.

  • Page, Julian. (2003). Implementing Lean Manufacturing Techniques.

  • RNA Automation. (2020). Poka-Yoke in Manufacturing. Retrieved from https://www.rnaautomation.com/blog/poka-yoke-in-manufacturing/.

  • James P Womack and Daniel T Jones. (March 1, 2003) Lean Thinking, 2nd Edition, ISBN 978-0-7432-4927-0.

  • Manos, Tony (June 2006). “Value Stream Mapping-an Introduction” (PDF). Quality Progress. American Society for Quality. p. 64.

  • Merrill Douglas (June 2013). “The Lean Supply Chain: Watch Your Waste Line”. Inbound logistics.

  • Christine Wheeler. (Feb 17, 2014). Eliminating 7 types of waste with 5s methodology. Retrieved from https://www.newcastlesys.com/blog/bid/336185/eliminating-7-types-ofwastewith-5s-methodology.

  • Mckinsey. (October 27, 2016). Supply chain 4.0-the next generation digital supply chain. Retrieved from https://www.mcki n s e y. com/business-functions/operations/our-insights/supply-chain-40--the-next-generation-digital-supply-chain.

  • Ottomotors. (Aug 24, 2017). Advantages of one piece flow manufacturing. Retrieved from https://ottomotors.com/blog/advantages-of-one-piece-flow-manufacturing.

  • Ben Mulholland. (January 5, 2018). How one piece flow can reduce your operation time by 96%? Retrieved from https://www.process.st/one-pieceflow/.

  • Villanovau. (Feb 6, 2018). Heijunka. Retrieved from https://www.villanovau.com/resources/six-sigma/heijunka/.

  • Rever team. (January 29, 2019). What is kaizen definition? Retrieved from https://reverscore.com/what-is-kaizen-definition/.

  • Tanya. (February 12, 2019). Lean systems and waste elimination. Retrieved from https://www.setpointusa.com/blog/lean-systemswasteelimination/#:~:text=Waste%20elimination%20is%20one%20of,is%20and%20where%20it%20exists.

  • Cleartax. (Jun 05, 2020). Just in time jit inventory management. Retrieved from https://cleartax.in/s/just-in-time-jitinventorymanagement.

  • Martin Murray. (October 12, 2020). What is just in time supply chain? Retrieved from https://www.thebalancesmb.com/just-in-time-jit-2221262.

  • Kenge, Rohit. & Khan, Zafar. (2020). A case study of industry 4.0 implementation in manufacturing industry. The Clarion- International Multidisciplinary Journal. 9(2). 6-11.10.5958/2277-937X.2020.00010.6.


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  • Manufacturing Excellence Model To Solve Operational Risks Due To Product Demand Variations

Abstract Views: 319  |  PDF Views: 0

Authors

Rohit Kenge
Sandip University, Nashik, India
Zafar Khan
Sandip University, Nashik, India

Abstract


The dynamic product demand impacts the manufacturing supply cycle by creating some operational risks like high inventories, excess manpower, and underutilization of machines, etc. Business firms or companies get impacted financially due to the dynamic product demand with issues like rising finish goods, raw material, and in-process stocks or inventories, inefficient usage of resources like machines, water, and people, and excess or less manpower or job cuts.

We studied the lean manufacturing principle in a literature survey to understand the concept of the manufacturing excellence at the product manufacturing and its deployment to solve the above-listed issues due to product demand variations. Further, in research methodology, we considered the independent variable as dynamic product demand and the dependent variable as operational risks like high inventories, excess manpower, and underutilization of machines. We plotted the value stream map for the selected product manufacturing with daily demand 25 and 40 numbers to understand the operation risks that occur after changing the demands.

We proposed consolidated manufacturing excellence models for solving the operational risks and after deployment of them; we again plotted the value stream map for the selected product manufacturing with daily demand 25 and 40 numbers. We got gain of in the case of the daily 25 demand, total lead time reduced from 14.6 to 7.82 days that is 46.44% for in-house product manufacturing and in the case of the daily 40 demand, total lead time reduced from 26.18 to 15.18 days that is 42.01%. Total lead time in both cases is reduced by +40% that helped product manufacturing.

We conclude this research study as our manufacturing excellence models are successful in delivering the expected results at our selected product manufacturing.


Keywords


VSM, Lean, Manufacturing Excellence Model, Inventory, Operational Risks.

References





DOI: https://doi.org/10.23862/kiit-parikalpana%2F2020%2Fv16%2Fi1-2%2F204565