Optimizing Resource Allocation and Efficiency in Production Planning for Sustainable Manufacturing: A Case Study in the Post-Pandemic Economy
DOI:
https://doi.org/10.35335/emod.v15i2.44Keywords:
Resource Allocation, Efficiency Optimization, Production Planning, Sustainable Manufacturing, Post-Pandemic Economy, Supply Chain CollaborationAbstract
Sustainable manufacturing faces new difficulties and opportunities in the post-pandemic economy. Given the changing manufacturing scene, this research addresses production planning resource allocation and efficiency. The study incorporates sophisticated technology, lean manufacturing, data analytics, and supply chain collaboration. A mathematical model for resource allocation and efficiency optimization starts the investigation. The model incorporates production capacity, demand fulfillment, unit costs, and resource efficiencies. An objective function minimizes production cost while meeting demand and resource capacity limits. The model supports optimization and decision-making. Research shows that modern technologies improve resource allocation and efficiency. Automation, robots, and AI algorithms improve operations, minimize errors, and enable data-driven decision-making. Lean manufacturing, including waste reduction and just-in-time inventory management, improves resource usage and efficiency. Data analytics aids production planning decision-making. Real-time production bottleneck, energy consumption, and resource utilization data informs proactive modifications. Data analytics improve decision-making. Sustainable manufacturing requires supply chain collaboration. Stakeholder collaboration, synchronized planning, and information exchange align production plans, reduce disruptions, and boost supply chain efficiency. The study promotes collaboration for long-term sustainability. The study admits numerous limitations but offers significant observations and recommendations. Context-specific application, data availability and quality, and real-world production system complexity are examples. These limitations should be addressed in future study. This research optimizes resource allocation and production planning for sustainable post-pandemic manufacturing. Advanced technology, lean manufacturing, data analytics, and supply chain collaboration can improve resource utilization, cut costs, and contribute to environmental sustainability. The findings support real-world industrial strategy development.
References
Alves, J. R. X., & Alves, J. M. (2015). Production management model integrating the principles of lean manufacturing and sustainability supported by the cultural transformation of a company. International Journal of Production Research, 53(17), 5320-5333.
Bansal, P., & Roth, K. (2000). Why companies go green: A model of ecological responsiveness. Academy of management journal, 43(4), 717-736.
Bell, S. (2005). Lean enterprise systems: using IT for continuous improvement. John Wiley & Sons.
Bhamu, J., Khandelwal, A., & Sangwan, K. S. (2013). Lean manufacturing implementation in an automated production line: a case study. International Journal of Services and Operations Management, 15(4), 411-429.
Bhushan, R. K. (2013). Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites. Journal of cleaner production, 39, 242-254.
Bi, Z. M., & Wang, L. (2012). Optimization of machining processes from the perspective of energy consumption: A case study. Journal of manufacturing systems, 31(4), 420-428.
Bibri, S. E. (2019). The anatomy of the data-driven smart sustainable city: instrumentation, datafication, computerization and related applications. Journal of Big Data, 6(1), 1-43.
Bibri, S. E. (2020). Compact urbanism and the synergic potential of its integration with data-driven smart urbanism: An extensive interdisciplinary literature review. Land Use Policy, 97, 104703.
Bibri, S. E., & Krogstie, J. (2020). The emerging data–driven Smart City and its innovative applied solutions for sustainability: The cases of London and Barcelona. Energy Informatics, 3, 1-42.
Bunse, K., Vodicka, M., Schönsleben, P., Brülhart, M., & Ernst, F. O. (2011). Integrating energy efficiency performance in production management–gap analysis between industrial needs and scientific literature. Journal of Cleaner Production, 19(6-7), 667-679.
Choomlucksana, J., Ongsaranakorn, M., & Suksabai, P. (2015). Improving the productivity of sheet metal stamping subassembly area using the application of lean manufacturing principles. Procedia Manufacturing, 2, 102-107.
de Sousa Jabbour, A. B. L., Jabbour, C. J. C., Foropon, C., & Godinho Filho, M. (2018). When titans meet–Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors. Technological Forecasting and Social Change, 132, 18-25.
Di Vaio, A., & Varriale, L. (2020). Blockchain technology in supply chain management for sustainable performance: Evidence from the airport industry. International Journal of Information Management, 52, 102014.
Dincer, I. (2000). Renewable energy and sustainable development: a crucial review. Renewable and sustainable energy reviews, 4(2), 157-175.
Diran, D., Hoppe, T., Ubacht, J., Slob, A., & Blok, K. (2020). A data ecosystem for data-driven thermal energy transition: Reflection on current practice and suggestions for re-design. Energies, 13(2), 444.
Duflou, J. R., Sutherland, J. W., Dornfeld, D., Herrmann, C., Jeswiet, J., Kara, S., ... & Kellens, K. (2012). Towards energy and resource efficient manufacturing: A processes and systems approach. CIRP annals, 61(2), 587-609.
Esmaeilian, B., Behdad, S., & Wang, B. (2016). The evolution and future of manufacturing: A review. Journal of manufacturing systems, 39, 79-100.
Esmaeilian, B., Behdad, S., & Wang, B. (2016). The evolution and future of manufacturing: A review. Journal of manufacturing systems, 39, 79-100.
Fiksel, J. (2006). Sustainability and resilience: toward a systems approach. Sustainability: Science, Practice and Policy, 2(2), 14-21.
Garetti, M., & Taisch, M. (2012). Sustainable manufacturing: trends and research challenges. Production planning & control, 23(2-3), 83-104.
Gunasekaran, A., Forker, L., & Kobu, B. (2000). Improving operations performance in a small company: a case study. International Journal of Operations & Production Management, 20(3), 316-336.
Hamilton, H., Henry, R., Rounsevell, M., Moran, D., Cossar, F., Allen, K., ... & Alexander, P. (2020). Exploring global food system shocks, scenarios and outcomes. Futures, 123, 102601.
He, J., Li, Z., Zhang, X., Wang, H., Dong, W., Chang, S., ... & Zhao, X. (2020). Comprehensive report on China's long-term low-carbon development strategies and pathways. Chinese Journal of Population, Resources and Environment, 18(4), 263.
Heilig, L., Schwarze, S., & Voß, S. (2017). An analysis of digital transformation in the history and future of modern ports.
Himanen, L., Geurts, A., Foster, A. S., & Rinke, P. (2019). Data‐driven materials science: status, challenges, and perspectives. Advanced Science, 6(21), 1900808.
Hodge, G. L., Goforth Ross, K., Joines, J. A., & Thoney, K. (2011). Adapting lean manufacturing principles to the textile industry. Production Planning & Control, 22(3), 237-247.
Hopwood, B., Mellor, M., & O'Brien, G. (2005). Sustainable development: mapping different approaches. Sustainable development, 13(1), 38-52.
Huson, M., & Nanda, D. (1995). The impact of just‐in‐time manufacturing on firm performance in the US. Journal of Operations Management, 12(3-4), 297-310.
Iacovidou, E., Velis, C. A., Purnell, P., Zwirner, O., Brown, A., Hahladakis, J., ... & Williams, P. T. (2017). Metrics for optimising the multi-dimensional value of resources recovered from waste in a circular economy: A critical review. Journal of Cleaner Production, 166, 910-938.
Javadian Kootanaee, A., Babu, K. N., & Talari, H. (2013). Just-in-time manufacturing system: from introduction to implement. Available at SSRN 2253243.
Jayal, A. D., Badurdeen, F., Dillon Jr, O. W., & Jawahir, I. S. (2010). Sustainable manufacturing: Modeling and optimization challenges at the product, process and system levels. CIRP Journal of Manufacturing Science and Technology, 2(3), 144-152.
Jimmerson, C., Weber, D., & Sobek II, D. K. (2005). Reducing waste and errors: piloting lean principles at Intermountain Healthcare. The Joint Commission Journal on Quality and Patient Safety, 31(5), 249-257.
Jones, M. M., Abrams, D., & Lahiri, A. (2020). Shape the Future: how the social sciences, humanities and the arts can SHAPE a positive, post-pandemic future for peoples, economies and environments. Journal of the British Academy, 8, 167-266.
Jovane, F., Yoshikawa, H., Alting, L., Boer, C. R., Westkamper, E., Williams, D., ... & Paci, A. M. (2008). The incoming global technological and industrial revolution towards competitive sustainable manufacturing. CIRP annals, 57(2), 641-659.
Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International journal of operations & production management.
Keane, A., Ochoa, L. F., Borges, C. L., Ault, G. W., Alarcon-Rodriguez, A. D., Currie, R. A., ... & Harrison, G. P. (2012). State-of-the-art techniques and challenges ahead for distributed generation planning and optimization. IEEE Transactions on Power Systems, 28(2), 1493-1502.
Kootanaee, A. J., Kootanaee, S. G., Solehboni, Z. A., & Kootanaee, A. J. (2013). Just-in-Time manufacturing system, Revolution in Management Accounting From concept to implement. International Review of Management and Business Research, 2(1), 133-148.
Lenzen, M., Li, M., Malik, A., Pomponi, F., Sun, Y. Y., Wiedmann, T., ... & Yousefzadeh, M. (2020). Global socio-economic losses and environmental gains from the Coronavirus pandemic. PloS one, 15(7), e0235654.
Manners-Bell, J. (2017). Supply chain risk management: understanding emerging threats to global supply chains. Kogan Page Publishers.
Moriarty, P., & Honnery, D. (2020). New approaches for ecological and social sustainability in a post-pandemic world. World, 1(3), 191-204.
Nallusamy, S. (2016). Efficiency enhancement in CNC industry using value stream mapping, work standardization and line balancing. International Journal of Performability Engineering, 12(5), 413-422.
Ness, D. A., & Xing, K. (2017). Toward a resource‐efficient built environment: A literature review and conceptual model. Journal of Industrial Ecology, 21(3), 572-592.
Okafor-Yarwood, I., Kadagi, N. I., Miranda, N. A., Uku, J., Elegbede, I. O., & Adewumi, I. J. (2020). The blue economy–cultural livelihood–ecosystem conservation triangle: the African experience. Frontiers in Marine Science, 7, 586.
Oliveira, J., Sá, J. C., & Fernandes, A. (2017). Continuous improvement through" Lean Tools": An application in a mechanical company. Procedia Manufacturing, 13, 1082-1089.
Omer, A. M. (2008). Energy, environment and sustainable development. Renewable and sustainable energy reviews, 12(9), 2265-2300.
Orsato, R. J. (2006). Competitive environmental strategies: when does it pay to be green?. California management review, 48(2), 127-143.
Peck, H. (2005). Drivers of supply chain vulnerability: an integrated framework. International journal of physical distribution & logistics management.
Porter, M. E., & Linde, C. V. D. (1995). Toward a new conception of the environment-competitiveness relationship. Journal of economic perspectives, 9(4), 97-118.
Sarkis, J. (2001). Manufacturing’s role in corporate environmental sustainability‐Concerns for the new millennium. International Journal of Operations & Production Management, 21(5/6), 666-686.
Sauvé, S., Bernard, S., & Sloan, P. (2016). Environmental sciences, sustainable development and circular economy: Alternative concepts for trans-disciplinary research. Environmental development, 17, 48-56.
Shrouf, F., Ordieres-Meré, J., García-Sánchez, A., & Ortega-Mier, M. (2014). Optimizing the production scheduling of a single machine to minimize total energy consumption costs. Journal of Cleaner Production, 67, 197-207.
Stock, T., & Seliger, G. (2016). Opportunities of sustainable manufacturing in industry 4.0. procedia CIRP, 40, 536-541.
Sudhakara, P. R., Sałek, R., Venkat, D., & Chruzik, K. (2020). Management of non-value-added activities to minimize lead time using value stream mapping in the steel industry. Acta Montanistica Slovaca, 25(3).
Taj, S., & Berro, L. (2006). Application of constrained management and lean manufacturing in developing best practices for productivity improvement in an auto‐assembly plant. International Journal of Productivity and Performance Management, 55(3/4), 332-345.
Tersine, R. J., & Hummingbird, E. A. (1995). Lead‐time reduction: the search for competitive advantage. International Journal of Operations & Production Management, 15(2), 8-18.
Theyel, G. (2000). Management practices for environmental innovation and performance. International journal of operations & production management, 20(2), 249-266.
Tilman, D. (1999). Global environmental impacts of agricultural expansion: the need for sustainable and efficient practices. Proceedings of the national Academy of Sciences, 96(11), 5995-6000.
Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International journal of production economics, 176, 98-110.
Wu, L., Yue, X., Jin, A., & Yen, D. C. (2016). Smart supply chain management: a review and implications for future research. The International Journal of Logistics Management.
Xu, F., Sun, J., Konda, N. M., Shi, J., Dutta, T., Scown, C. D., ... & Singh, S. (2016). Transforming biomass conversion with ionic liquids: process intensification and the development of a high-gravity, one-pot process for the production of cellulosic ethanol. Energy & Environmental Science, 9(3), 1042-1049.
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