Call for Paper - Upcoming Issues

A Proposed Model for Inventory Analysis and Its Productivity Implications of Medium-Scale Industries

International Journal of Mechanical Engineering
© 2025 by SSRG - IJME Journal
Volume 12 Issue 7
Year of Publication : 2025
Authors : S. Hariharan, Partha Sarathi Chakraborthy, S. Nallusamy, K. Manogar
10.14445/23488360/IJME-V12I7P102
pdf
How to Cite?

S. Hariharan, Partha Sarathi Chakraborthy, S. Nallusamy, K. Manogar, "A Proposed Model for Inventory Analysis and Its Productivity Implications of Medium-Scale Industries," SSRG International Journal of Mechanical Engineering, vol. 12,  no. 7, pp. 7-17, 2025. Crossref, https://doi.org/10.14445/23488360/IJME-V12I7P102

Abstract:

Medium-sized manufacturing industries struggle with inventory management due to higher operating costs, inefficiencies, and lower profitability. This research study introduces Customer Identity and Access Management (CIAM), a proposed model for inventory analysis. This inventory management methodology combines traditional methods with automated technology, real-time monitoring, and predictive analytics. The concept requires Just-In-Time (JIT) inventory management, sensors connected to the Internet of Things (IoT) for real-time tracking, sophisticated demand forecasting algorithms, automated replenishment systems connected to ERP platforms, and other components. The approach involves developing optimization and forecasting algorithms, collecting production and inventory data, testing the model in a subset of industries, and evaluating its effectiveness. The proposed method aims to improve inventory turnover, production efficiency, operational expenditures, and data-driven decision-making. After the pilot program is up and running, the next stages involve rolling it out to the rest of the industry, continuously optimizing it, training all stakeholders, and monitoring their progress. In addition to filling in the essential gaps in inventory management for medium-scale enterprises, this integrated solution lays the groundwork for long-term productivity gains by using resources and implementing flexible supply chain methods.

Keywords:

RFID, Inventory analysis, CIAM, Supply chain, Medium scale industry, Stakeholder.

References:

[1] Rashmi Ranjan Panigrahi et al, “Management of Inventory for Firms’ Efficiency – A Study on Steel Manufacturing Industry,” Journal of Advances in Management Research, vol. 19, no. 3, pp. 443-463, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Ali Khaleel Dhaiban, and Ehab A. Mahmood, “The Effect of Initial Inventory Level on the Rates of Deteriorating and Production,” SSRG International Journal of Economics and Management Studies, vol. 5, no. 2, pp. 12-15, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[3] R. Chopra et al., “Utilization of ERP Systems in the Manufacturing Industry for Productivity Improvement,” Materials Today: Proceedings, vol. 62, pp. 1238-1245, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Suleiman Ibrahim Shelash Mohammad et al., “Impact of Crude Oil Price Volatility on Procurement and Inventory Strategies in the Middle East,” International Journal of Energy Economics and Policy, vol. 15, no. 2, pp. 715-727, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[5] A. Ramadan et al., “Managerial Competence and Inventory Management in SME Financial Performance: A Hungarian Perspective,” Journal of Statistics Applications & Probability, vol. 13, no. 3, pp. 859-870, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Rui Xie et al., “Effects of Financial Agglomeration on Green Total Factor Productivity in Chinese Cities: Insights from an Empirical Spatial Durbin Model,” Energy Economics, vol. 101, pp. 1-9, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[7] K. Balakannan et al., “Performance Evaluation of Supply Chain and Logistics Management System using Balanced Score Card for Efficiency Enhancement in Indian Automotive Industries,” Indian Journal of Science and Technology, vol. 9, no. 1, pp. 1-9, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Giacomo Damioli, Vincent Van Roy, and Daniel Vertesy, “The Impact of Artificial Intelligence on Labor Productivity,” Eurasian Business Review, vol. 11, pp. 1-25, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Van K. Nguyen, Riccardo Natoli, and Sarath Divisekera, “Innovation and Productivity in Tourism Small and Medium Enterprises: A longitudinal Study,” Tourism Management Perspectives, vol. 38, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Suminah Suminah et al., “Determinants of Micro, Small, and Medium-Scale Enterprise Performers’ Income during the Covid-19 Pandemic Era,” Heliyon, vol. 8, no. 7, pp. 1-10, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Zhang Tian Xiang, and Chin Jeng Feng, “Implementing Total Productive Maintenance in a Manufacturing Small or Medium-Sized Enterprise,” Journal of Industrial Engineering and Management, vol. 14, no. 2, pp. 152-175, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Mohammad Rakibul Islam Bhuiyan, “The Challenges and Opportunities of Post-COVID Situation for Small and Medium Enterprises (SMEs) in Bangladesh,” PMIS Review, vol. 2, no. 1, pp. 141-159, 2023.
[Google Scholar]
[13] André de Mendonça Santos et al., “Industry 4.0 as an Enabler of Sustainability for Small and Medium Enterprises,” Academia Revista Latinoamericana de Administration, vol. 37, no. 2, pp. 204-226, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Armando Elizondo-Noriega, Naveen Tiruvengadam, and David Guemes-Castorena, “Impact of RFID Implementation on Operational Productivity of a Manufacturing Firm: A Simulation-based Study,” International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 15, pp. 555-575, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Daniel E. Ufua et al., “Implementing Just-in-time Inventory Management to Address Contextual Operational Issues: A Case Study of a Commercial Livestock Farm in Southern Nigeria,” The TQM Journal, vol. 34, no. 6, pp. 1752-1771, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Yasaman Mashayekhy et al., “Impact of Internet of Things (IoT) on Inventory Management: A Literature Survey,” Logistics, vol. 6, no. 2, pp. 1-19, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Friday Ugbebor, Michael Adeteye, and John Ugbebor, “Automated Inventory Management Systems with IoT Integration to Optimize Stock Levels and Reduce Carrying Costs for SMEs: A Comprehensive Review,” Journal of Artificial Intelligence General Science, vol. 6, no. 1, pp. 306-340, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Nisreen Ameen et al., “Customer Experiences in the Age of Artificial Intelligence,” Computers in Human Behavior, vol. 114, pp. 1-14, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Merlin Stone et al., “Artificial Intelligence (AI) in Strategic Marketing Decision-Making: A Research Agenda,” The Bottom Line, vol. 33, no. 2, pp. 183-200, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Bhimrao M. Ghodeswar, “Building Brand Identity in Competitive Markets: A Conceptual Model,” Journal of Product & Brand Management, vol. 17, no. 1, pp. 4-12, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Seshadri Tirunillai, and Gerard J. Tellis, “Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation,” Journal of Marketing Research, vol. 51, no. 4, pp. 463-479, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Artur M. Pereira et al., “Customer Models for Artificial Intelligence-Based Decision Support in Fashion Online Retail Supply Chains,” Decision Support Systems, vol. 158, pp. 1-34, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Felipe Barrera, Marina Segura, and Concepción Maroto, “Multiple Criteria Decision Support System for Customer Segmentation using a Sorting Outranking Method,” Expert Systems with Applications, vol. 238, pp. 1-17, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Paul Temporal, Advanced Brand Management: Managing Brands in a Changing World, Second Edition, John Wiley & Sons, pp. 1-18, 2021.
[Google Scholar] [Publisher Link]
[25] Michela Matarazzo et al., “Digital Transformation and Customer Value Creation in Made in Italy SMEs: A Dynamic Capabilities Perspective,” Journal of Business Research, vol. 123, pp. 642-656, 2021.
[CrossRef] [Google Scholar] [Publisher Link]