It is acknowledged that the rapid advancement in technological developments has driven digital transformation in organizations. Thus, the conventional value chain management and control approaches are shifting towards smart, data-driven management and control systems through the digitalization of product/service life cycle. This study contributes to the body of knowledge with a comprehensive literature review of Industry 4.0 technologies, and its implications on operations management research. Moreover, due to the multidisciplinary nature of Industry 4.0, it was imperative to reveal, discern, and discover the interconnected research themes with operations management to identify future research trends. The synthesis of existing literature illustrates that digitalization, end-to-end value chains, real-time monitoring and control systems, smart management systems and intelligent decision-making, collaborative and sustainable ecosystems, dynamic capabilities, and intelligent organizations are all future research trends of Operations Management 4.0.
Top1. Introduction
The 4th industrial revolution is considered the biggest structural change humankind has witnessed over the past 250 years. Industry 4.0 has largely transformed the way we live, consume, work, invest, trade, and how we relate to one another. This new paradigm combines the physical, digital, and virtual world into what is called Cyber-Physical Systems (CPS). Thus, has disruptive innovation effects in every industry. Nowadays, smart and connected technologies can be embedded within machines, devices, resources, people, and products. Thus, end-to-end value chains will become not only interconnected and entirely integrated, but also can communicate, analyse, and use data in real-time to drive intelligent actions autonomously back in the physical world. Industry 4.0 is marked by the emergence of smart technologies such as the Internet of Things/Services (IoT/IoS), Wearables, Digital Twin, Augmented Reality (AR), Artificial Intelligence (AI), Robotics, Big Data Analytics, 3D Printing (Henrik von Scheel, 2019). Yet, till now Industry 4.0 is still considered in its beginning stages (Awan, Sroufe & Shahbaz, 2021).
The integration of advanced operations and production techniques with smart technologies has created a digitalized enterprise with intelligent, real-time, decision-making capabilities across operational and strategic levels (Choi et al., 2022). Industry 4.0 proven benefits in the literature, have motivated researchers to further understand data-driven ecosystems, intelligent human-machine interactions, business models innovation, sustainable value chains, and smart production/services. Accordingly, new hybrid concepts such as Smart Factory, Smart Products and Services, Maintenance 4.0, Logistics 4.0, Quality 4.0, Operator 4.0, and Sustainability 4.0 among others have emerged as new research topics (Cimini et al., 2020; Leng et al., 2021; Shi et al., 2020; Rifqi et al., 2021).
Moreover, the COVID-19 crisis has accelerated businesses’ adjustments to the next normal. Organisations are rethinking the viability of its supply chain networks to increase its capabilities to deal with disruption risks, to sustain itself and survive in a rapidly changing environment. The next era is characterised by the fusion of physical, virtual and digital world. In this sense, firms are shifting their focus form only operations efficiency, into creating value through collaborative data-driven business models, smart end-to-end operations, and sustainable value chain management. As a result, the role of Industry 4.0 smart technologies has been reinforced to transform value chains into viable, intelligent and sustainable ecosystems (Yin & Ran, 2021; Sautter, 2021).
Industry 4.0 is driving the digitalisation of traditional operations and quality management systems, and enable transformation into smart management paradigms (Efimova & Briš, 2021). The incorporation of Industry 4.0 technologies into value chain activities will assist in the development of smart lean systems, intelligent, autonomous, and collaborative decision making systems integrated across the hieratical levels of the organisation to maximize value creation and achieve excellent performance (Eloot, Mancini & Patel, 2020; Reyes, Mula & Díaz-Madroñero, 2021). Yet, the nature and level of organisation’s tangible and intangible capabilities are key enablers in the creation of smart intelligent ecosystems. The tangible abilities include the physical and networking assets that create the intelligent, connected, and automated infrastructure. Whilst the intangible abilities consist of internal smart management techniques and adaptable production systems. In addition to external networking competencies to create smart innovative networks, and enable dynamic information sharing among stakeholders (Zhou et al., 2022).