Akıllı ve Sürdürülebilir Tedarik Zinciri Yönetiminin Hazırlık ve Olgunluk Düzeyinin Değerlendirilmesi için Geometrik Ortalamaya Dayalı Yeni Bir Model ÖnerisiSercan Demir, Mehmet Akif Gündüz, Turan Paksoy
Son yıllarda küreselleşme ve küresel rekabetteki artış, artan teknolojik büyüme hızı, müşteri taleplerindeki çeşitlilik ve tedarik zinciri süreçlerinin giderek karmaşıklaşması firmaların tedarik zinciri stratejilerine akıllı ve sürdürülebilir paradigmalar eklemelerine neden olmuştur. Tedarik zinciri oyuncuları arasındaki gerçek zamanlı bilgi paylaşımı ve zincirin her bir basamağının etkin koordinasyonu, tedarik zincirinin verimli şekilde yönetimi için önemli rol oynamaktadır. Bu da geleneksel tedarik zincirinden dijital tedarik zincirine dönüşüm ile mümkündür. Endüstri 4.0 olarak adlandırılan ve 2011 yılında Almanya’da doğan Dördüncü Sanayi Devrimi bilgi teknolojileri, nesnelerin interneti, yapay zeka, bulut bilişim teknolojisi, otonom araçlar, robotik sistemler, sensor ve otomasyon ağları, sanal ve arttırılmış gerçeklik gibi teknolojilerin üretim süreçlerine yoğun biçimde entegrasyonunu hedef alan yenilikçi bir paradigmadır. Ne var ki, Endüstri 4.0’a uyum ve uyum sonrası olgunluk dönemi birçok firma için beklenmedik problemlere yol açabilmektedir. Akıllı fabrikaların kurulmasında ve dijital dönüşümün uygulanmasında en büyük sorunlardan biri, Endüstri 4.0 yetkinliklerinin tüm operasyonlara eş zamanlı olarak etkin şekilde uygulanamamasıdır. Bu bağlamda, firmaların Endüstri 4.0’a hazırlık ve uyum sonrası olgunluk düzeylerinin niceliksel ölçümü ve değerlendirilmesi, üst yönetim için büyük önem arz etmektedir. Bu çalışmanın amacı firmaların Endüstri 4.0’a hazırlık ve olgunluk düzeylerinin daha iyi anlaşılıp ölçülebilmesi için, dijital tedarik zincirlerinin akıllı ve sürdürülebilir boyutta olgunluk düzeylerinin eş zamanlı ölçülebilmesine olanak sağlayan bir model önermektir. Modelin uygulandığı nümerik örnekte, her bir Endüstri 4.0 aracının sürdürülebilirlik boyutlarına ne derece uyum sağladığı belirlenmiştir. Örneğin, eklemeli imalat ve arttırılmış gerçeklik sürdürülebilirliğin ekonomik boyutunda yüksek olgunluk skoru alırken, çevresel ve sosyal boyutlara göre daha düşük skor almıştır. Benzer şekilde, yapay ve dikey sistem entegrasyonu her üç boyut için yüksek olgunluk seviyesinde iken, yapay zeka çok düşük olgunluk seviyesinde kalmıştır.
A New Evaluation Model for the Readiness and Maturity Level of Intelligent and Sustainable Supply Chain Management Based on Geometric MeanSercan Demir, Mehmet Akif Gündüz, Turan Paksoy
Recently, companies have added smart and sustainable paradigms to their supply chain strategies as a result of globalization and increased global competition, increasing technological growth rate, diversity in customer demands, and increasing complexity in supply chain processes. Real-time information sharing among supply chain players and the effective coordination of each step of the chain are critical for efficient supply chain management. This is made possible by the transition from the traditional supply chain to the digital supply chain. The Fourth Industrial Revolution, also known as Industry 4.0, was coined for the first time in Germany in 2011. It is an innovative paradigm with the goal of intensely integrating technologies, such as information technologies, the Internet of Things, artificial intelligence, cloud computing technology, autonomous vehicles, robotic systems, sensor and automation networks, and virtual and augmented reality into production processes. However, for many companies, the adaptation of Industry 4.0 and the subsequent maturity period may present unexpected challenges. One of the most difficult challenges in establishing smart factories and implementing digital transformation is that Industry 4.0 competencies cannot be effectively applied to all operations simultaneously. In this context, quantitative measurement and evaluation of firms’ maturity levels following Industry 4.0 preparation and adaptation is critical for senior management. The goal of this study is to propose a model for measuring the maturity level of digital supply chains while considering smart and sustainable dimensions. We determined the extent to which each Industry 4.0 tool was compatible with the sustainability dimensions in the numerical example where the model was applied. For example, although additive manufacturing and augmented reality receive high scores in the economic dimension of sustainability, they receive lower scores in the environmental and social dimensions. Similarly, although horizontal and vertical systems integration has high levels of maturity in all three sustainability dimensions, artificial intelligence has an exceptionally low level of maturity.
Since the beginning of industrialization, technological leaps have resulted in paradigm shifts known as “Industrial Evolutions.” So far, three industrial revolutions have led to paradigm shifts in manufacturing: mechanization through steam power, mass production in assembly lines, and automation by information technology. Recently, researchers and policymakers worldwide have increasingly called for the term Industry 4.0 to be used to describe the impending changes that the industries will face because of the new era of digitization. This revolution is based on the increased availability of digital connectivity technologies, which are being used to reorganize supply chains. Industry 4.0 promotes decentralization of decision-making and information distribution in each entity that makes up the overall system. This decentralization promotes the flexibility and agility of systems by increasing their responsiveness and autonomy. Simultaneously, companies are confronted with new opportunities and challenges as public awareness of social, environmental, and economic sustainability concerns grows. The emergence of smart technologies calls into question business leaders’ models and imposes two major challenges. The first challenge is to envision how these technologies can be used to transform supply chain processes, and the second is to master these smart technologies to create new products or services. Ensuring sustainability while matching these critical business skills will be a critical issue in this new era.
Various maturity models are available in the literature to support companies in their digitization efforts. Essentially, these models are concerned with the organization’s digital maturity. However, available readiness maturity models do not address sustainability issues and overlook a fundamental aspect of the digital revolution: the opportunity to redefine the company’s mission through a strategic positioning review. As a result of this redefinition, companies that have traditionally been oriented toward business objectives are being compelled to refocus their activities on promoting social welfare, environmental responsibility, and economic value generation. We propose a novel, smart, and sustainable supply chain readiness and maturity approach in this study. In the context of supply chain sustainability in economic, environmental, and social dimensions, our model conceptualizes the extent to which Industry 4.0 tools are understood (understanding score), applied (implementation score), and contribute to organizational goals (development score). The awareness and knowledge of the available smart technologies are displayed in the understanding dimension. Moreover, the adoption of smart technologies within supply chain processes is implied by the implementation dimension. The third dimension, development, represents the organization’s readiness to progress with its digital transformation. Our model consists of five steps. A questionnaire is used to collect scores on understanding, implementation, and contribution to development in three sustainability dimensions for each of the 12 tools in the first step. As a result, the initial tool maturity matrix is obtained, with the rows consisting of 12 Industry 4.0 tools and the columns consisting of understanding, implementation, and development scores in the three dimensions of sustainability. The tool-dimension score for each of the 12 Industry 4.0 tools is calculated in the second step using the initial tool maturity matrix values by taking the geometric mean of the three dimensions of sustainability. At the third and fourth steps, a total readiness and maturity score is calculated for each sustainability dimension and the enterprise, respectively. Finally, the fifth step computes an overall smart and sustainable supply chain readiness and maturity score. To demonstrate the applicability of the proposed model, we conduct a case study in the automotive manufacturing industry. By combining its three dimensions, we can assess an organization’s readiness and maturity to begin the transition to Industry 4.0 while taking sustainability concerns into account. Our model enables decision-makers to assess the current situation using a readiness and maturity approach, measure performance, and set goals to support continuous development and innovation activities in the adoption of smart technologies to supply chain processes.