Enhancing Local Bottle Manufacturing through Lean Principles and Simulation

This study focuses on improving a local bottle manufacturing operation by implementing Lean principles and discrete event simulation. It addresses challenges in the industry, presents a case study of an SME bottle manufacturer, and explores opportunities for enhancement through computer simulation using ARENA software to optimize production systems. Key factors such as system performance, inspection-to-production ratio, and cost utilization are analyzed to boost efficiency and productivity.

• Bottle Manufacturing
• Lean Principles
• Simulation
• SME
• Efficiency

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1. A STUDY ON THE IMPROVEMENT OF A LOCAL BOTTLE MANUFACTURING OPERATION: DEPLOYMENT OF LEAN PRINCIPLES AND DISCRETE EVENT SIMULATION Ezekiel Yorke1*, Boppana V. Chowdary2, Jainarine Bansee3 Ezekiel Yorke, The Ministry of Works and Transport Boppana V. Chowdary, Faculty of Engineering, The University of the West Indies Jainarine Bansee, Faculty of Engineering, The University of the West Indies IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

2. INTRODUCTION Why This Field of Research in Manufacturing? TT $919 Million S.M.E. 5.6% TT $702 Million Increased Revenue from 2010 to 2014 Accounts for 30% the GDP of T&T Continued Growth in the Food and Beverage Industry in 2018 IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

3. CHALLENGES IN THE INDUSTRY Despite the Successes ? 9% Financial and Infrastructural Challenges in SMEs Increased Competition on the Global Market Observed Stagnation in the Manufacturing Sector IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

4. CASE STUDY: SME BOTTLE MANUFACTURER COMPANY X Fabrication of Plastic Preforms Plastic Injection Moulding (PIM) A process of fabricating parts of complex geometries at high rates using injection moulding machines IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

5. CASE STUDY: SME BOTTLE MANUFACTURER CHALLENGES FACED OPPORTUNITIES FOR IMPROVEMENT? M1 44 Produced 44 Inspected 1 Inspected 44 Produced Raw Material M2 Raw Material 32 Produced 1 Inspected 32 Produced 32 Inspected 11% Reduced Capacity Reduction in System Performance Low Inspection to Production Ratio Increased CU and Reduced Cost Utilisation (CU) High Inspection to Production Ratio Increase in System Performance IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

6. CASE STUDY: SME BOTTLE MANUFACTURER How Can This Be Done? Computer Simulation Using ARENA Simulation Software Improving Performance in Plastic Manufacturing Simulate and Improve Bottle- filling Production Systems Key Performance Indicators (KPI) Value Added Time (VAT) Waiting Time (WT) Operational Cost IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

7. CASE STUDY: SME BOTTLE MANUFACTURER How Can This Be Done? Lean Manufacturing (LM) Increase Quality and Efficiency Minimise Waste Reduce Cost IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

8. CASE STUDY: SME BOTTLE MANUFACTURER AIM To improve the PIM operations of local SME bottle manufacturer using LM Principles and Simulation OBJECTIVES Propose LM Strategies with financial validation Review the PIM operations Develop a PIM conceptual framework Design a Steady State Simulation Model DELIVERABLES High Inspection to Production Ratio Increase in System Performance Increased CU and Reduced Cost IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

9. CASE STUDY: SME BOTTLE MANUFACTURER Product Types Exit System for Storage and Distribution Transport Product Batches Enter Product Type 1 (P1) Injection Molding Process 1 (Yes) Transfer Product on Conveyor Line 1 Inspect Product Line 1 Are Product Types Defective? Transfer Product on Conveyor Line 2 Inspect Product Line 2 (No) Enter Product Type 2 (P2) Injection Molding Process 2 Discard Defective Product Types FLOW OF PIM OPERATIONS IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

10. CASE STUDY: SME BOTTLE MANUFACTURER Simulation Model in ARENA Data Collected and Used in Model Inter-Arrival Times Processing Times Input Times Raw Material (P1 & P2) PIM Machines 1 & 2 Technicians Resources Assign Modules Decision Modules Routing Simulated for 12 Months Run Time IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

11. CASE STUDY: SME BOTTLE MANUFACTURER Presentation and Analysis of Results after a Twelve Month Period 39% IMP1 VAT 33% IMP2 KPI 60% IMP1 WT 66% IMP2 IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

12. CASE STUDY: SME BOTTLE MANUFACTURER Deploying LM Principles Strategy 1 (S1) (Heijunka) Replaced the older PIM 1 Machine with a second PIM 2 Machine Strategy 2 (S2) (Kanban) Addition of Imaging Sensors within the Inspection Process Combined input routes for raw materials of similar types (P1 & P2) Added a decision module into routes to simulate a smart routing system Strategy 3 (S3) (Six Sigma) All Combined Strategies Strategy 2 & 3 Strategy 1 & 2 Strategy 1 & 3 IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

13. CASE STUDY: SME BOTTLE MANUFACTURER Deploying LM Principles Presentation and Analysis of Results after a Twelve Month Period 1.E+04 2.E+04 9.E+03 2.E+04 8.E+03 2.E+04 VAT and NVAT [hours] 7.E+03 1.E+04 6.E+03 1.E+04 WT [hours] 5.E+03 1.E+04 4.E+03 8.E+03 3.E+03 6.E+03 2.E+03 4.E+03 1.E+03 2.E+03 0.E+00 0.E+00 Existing S1 S2 S3 S1&S2 S1&S3 S2&S3 S12&3 VAT NVAT WT 8080 9436 7888 8792 8124 0 3850 4617 8124 0 3850 4617 4236 0 4236 0 18090 13799 824 4741 824 4741 346 346 IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

14. CASE STUDY: SME BOTTLE MANUFACTURER WIP and Financial Comparison 149 2.E+06 148 1.E+06 147 1.E+06 Total Busy Cost [TTD] 146 1.E+06 Throughput 145 8.E+05 144 6.E+05 143 4.E+05 142 2.E+05 141 0.E+00 Existing S1 S2 S3 S1&S2 S1&S3 S2&S3 S12&3 WIP 3.22 2.77 0.88 1.33 0.88 1.33 0.49 0.49 Throughput 144 144 145 147 145 147 148 148 Cost [TTD] 1.E+06 1.E+06 1.E+06 6.E+05 1.E+06 6.E+05 6.E+05 5.E+05 IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

15. CONCLUSION What Have We Achieved? Increase in System Performance High Inspection to Production Ratio Increased CU and Reduced Cost Future Research - What More Must Be Done? Explore the Qualitative Barriers to LM (e.g. Culture) Investigate the Competitive Priorities of Manufacturing Firms in the Local Region Apply LM Principles and Simulation to more Manufacturing SMEs in the Local Region IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

16. REFERENCES Hong, Mei-Hsiu, Tzong-Ru (Jiun-Shen) Lee, Ching-Kuei Kao, and Per Hilletofth. 2015. "Setting Organisational Key Performance Indicators in the Precision Machine Industry." International Journal of Management, Knowledge and Learning 4 (2):26. Mohammed, Abdullah. 2017. "Don't Just Teach a Man to Fish: Are Our Caribbean SME Policies Fundamentally Wrong? ." Technology news from T&T, Last Modified December 11, 2017, accessed January 7. https://technewstt.com/sme-policies/. Oxford, Business Group. 2016. Trinidad and Tobago's food and beverage sector offers new potential. Russell, Suzana N., and Harvey H. Millar. 2014. "Competitive Priorities of Manufacturing Firms in the Caribbean." Journal of Business and Management 16 (10):10. doi: 10.9790/487X-161017282. Wilson, Lonnie. 2015. How to Implement Lean Manufacturing. 2 ed. New York, United States: McGraw-Hill Education. IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago

17. THANK YOU! IConETech-2020, Faculty of Engineering, The UWI, St. Augustine, Trinidad and Tobago