production and operations management
Mohammad Rahim Ramazanian; Marjan Khodaparast Nodehei; Reza Sheikh
Abstract
Digital transformation and Industry 4.0 have emerged as key drivers for enhancing competitiveness and improving product quality across various industries, particularly in the automotive parts sector. This research focuses on Guilan Province, examining the extent of Industry 4.0 technologies’ implementation ...
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Digital transformation and Industry 4.0 have emerged as key drivers for enhancing competitiveness and improving product quality across various industries, particularly in the automotive parts sector. This research focuses on Guilan Province, examining the extent of Industry 4.0 technologies’ implementation aimed at increasing product longevity. Initially, through qualitative content analysis of 35 articles published between 2016 and 2024, 16 sub-criteria were identified within four main groups. Subsequently, using the novel OPLO-POCOD method (Opportunity Lost Assessment Based on Distance in Polar Coordinate Space) and surveying 14 experts from 10 parts manufacturing companies, the performance of these companies was analyzed. The results indicated that criteria such as automated warehousing systems, inventory management automation, and blockchain-based tracking had the highest impact on increasing product lifespan, with the lowest opportunity loss values of 0.0231, 0.0242, and 0.0253, respectively. On the other hand, the physical-information integration of the supply chain using cloud computing is still in the early stages of implementation. This research uniquely combines qualitative analyses with the innovative OPLO-POCOD method, enabling precise ranking of companies and identification of execution gaps. The findings emphasize the importance of focusing on smart technologies to achieve more sustainable and competitive production, assisting managers and policymakers in prioritizing Industry 4.0 strategies. Overall, while automotive parts industries in Guilan have made progress in areas such as automated warehousing, there is a need to accelerate the implementation of new technologies like cloud computing to fully realize the benefits of Industry 4.0 and complete the digital transformation process.IntroductionIn the contemporary competitive landscape, enhancing production quality and adopting sustainable supply chain management strategies—particularly with an emphasis on extending product lifespan—have evolved into strategic imperatives. Increasing product longevity not only alleviates pressure on natural resources and mitigates environmental impacts but also significantly enhances the economic value of products. Industry 4.0, as a transformative paradigm, leverages smart technologies such as additive manufacturing, the Internet of Things (IoT), robotics, and artificial intelligence to provide unprecedented potential for achieving these objectives. This digital transformation, enabling real-time tracking throughout the entire product lifecycle, predictive maintenance optimization, and production personalization, directly contributes to extending the useful life of products. The integration of this concept with Industry 4.0 smart technologies substantially enhances the capacity to realize these goals. This is particularly critical in complex and capital-intensive industries such as automotive and auto parts manufacturing, where production quality is directly linked to safety and competitiveness. However, despite prevailing assertions regarding the role of Industry 4.0 in sustainable development, few studies have specifically examined the impact of smart technologies on product lifespan extension. Aiming to address this research gap, this study focuses on the auto parts manufacturing industry to identify key components for enhancing product longevity within the Industry 4.0 framework. Employing an innovative methodology—the Lost Opportunity Technique based on distance in polar coordinate space—it investigates the extent of implementation of these factors within the industry. The findings of this research are poised to provide industrial managers and policymakers with a strategic roadmap for developing more sustainable and competitive products.MethodologyThe present study is applied in purpose and descriptive-survey in terms of data collection, adopting a multiple case study approach. This research was conducted using a mixed-methods (qualitative-quantitative) approach in two phases. In the qualitative phase, content analysis and a systematic review of library sources and reputable databases from 2016 to 2024 were employed to identify the most influential factors affecting product lifespan extension, with an emphasis on smart technologies within Industry 4.0. In the quantitative phase, a researcher-developed questionnaire based on a ten-point scale and the novel “Opportunity Losses-Based Polar Coordinate Distance (OPLO-POCOD)” was used to collect field data from 10 active companies in the automotive parts industry in Guilan Province. Sampling was performed using targeted and snowball sampling methods, and the questionnaires were completed by 14 experts (production managers, IT managers, and production line supervisors) with at least five years of professional experience and familiarity with Industry 4.0 concepts. The reliability of the questionnaire was confirmed with a Cohen’s kappa coefficient of 0.743, and its validity was endorsed by specialists. Finally, the collected data were analyzed using the OPLO-POCOD technique, and the companies under study were ranked based on the identified criteria.FindingsThe findings of this study, conducted using a mixed-methods approach (qualitative content analysis and the OPLO-POCOD technique), reveal that the adoption of Industry 4.0 technologies plays a significant role in enhancing product longevity in the automotive parts manufacturing industry. In the qualitative phase, which involved the analysis of 35 studies published between 2016 and 2024, 16 key concepts were identified across four main criteria: additive manufacturing, the Internet of Things (IoT), robotics, and smart supply chain management. The reliability of this analysis was confirmed with a Cohen’s kappa coefficient of 0.743. In the quantitative phase, employing the novel OPLO-POCOD technique and surveys of 14 experts across 10 automotive parts manufacturing companies, the studied companies were ranked based on their level of adoption of Industry 4.0 technologies. The results indicated that Companies 4, 3, and 5 achieved the highest percentages of opportunity gained (94.4%, 94.3%, and 93.9%, respectively) and the lowest levels of lost opportunity (below 0.061), securing the top ranks. In contrast, Companies 7, 2, and 8, with the highest levels of lost opportunity (between 0.131 and 0.174), demonstrated the weakest performance in adopting these technologies. These findings underscore the direct impact of implementing Industry 4.0 technologies—particularly in additive manufacturing, the Internet of Things, and smart supply chain management—on extending product lifespan.Discussion and conclusionThe present study aimed to assess the level of Industry 4.0 implementation in automotive parts manufacturing companies in Guilan Province. The findings revealed that three criteria—automated warehouse systems, inventory management automation, and blockchain-based traceability, all falling within the domain of data transparency and tracking—were identified as the most effective factors in enhancing product longevity. These results indicate that in Iran’s industrial context, the most fundamental layers of digitalization serve as essential prerequisites for achieving higher-level objectives such as the circular economy. On the other hand, the findings demonstrate that despite relative progress in certain foundational technologies, significant challenges persist in smart supply chain management, rooted in infrastructural limitations and weaknesses in strategic coordination among supply chain actors. This study contributes to the academic discourse in several ways, including the development of a prioritized operational framework (OPLO-POCOD) for assessing industrial readiness, the identification of specific mechanisms effective within each criterion, and the adaptation of global findings to Iran’s specific industrial context. By bridging theoretical literature with practical industry requirements, this research provides a valuable roadmap for industrial managers and policymakers. Based on the research findings, it is recommended that industrial managers allocate resources toward improving smart supply chain management. Furthermore, policymakers are advised to facilitate the successful implementation of Industry 4.0 by developing national cloud platforms for supply chain integration, providing targeted incentives to companies committed to national standards, and establishing mandatory data exchange standards. For future research, it is suggested that emerging criteria such as human-robot collaboration be examined, the study be replicated in other national industries, fuzzy logic-based methods be employed, and causal methods be utilized to analyze relationships among the identified criteria.
