Resilience Maturity Assessment in Manufacturing Supply Chains

Industry 5.0 is a new vision for European industry with focus on human centricity, sustainability, and resilience. Due to that most research on Industry 5.0 concentrates on digital technologies, mainly because its relation to Industry 4.0, there is still limited and one-sided understanding of the concept. To enhance the competitiveness of manufacturing industries in Europe, companies need to develop their capabilities not only in digitalization, but also of human centricity, sustainability and resilience. Resilience, the capacity to withstand or to recover quickly from difficulties, is an important aspect due to war, pandemic, energy crisis and climate change crisis. Many manufacturing companies face major challenges in their supply chains, with limited availability of components, lack of critical virgin materials, high-cost growth, and high supply risk exposure. This research seeks to bring further understanding of the resilience dimension of the Industry 5.0 concept. It adds to the limited amount of research available on Industry 5.0. Also, manufacturing companies need to better understand how they can strengthen their resilience in the supply chains. This paper presents a tool that companies may use to evaluate their maturity, and identify improvement areas. The tool is assessed in three companies

Maturity Models in Industrial Internet: a Review

The introduction of assembly lines in industrial plants marked the beginning of the third industrial revolution. The support of information technology has enabled continuous progresses, up to the digitalisation of the processes. In this context, the further innovation characterised by the introduction of Cyber-Physical Systems and other enabling technologies has allowed the fourth industrial revolution. Proposed by the German government, Industry 4.0 appealed to both researchers and practitioners. Since the appearance of the term Industry 4.0, the linked-term Industrial Internet has been introduced to indicate the technology stack and knowledge management required by Industry 4.0. Industrial Internet makes a factory smart by applying advanced information and communication systems and future-oriented technologies, as well as new principles of knowledge management. Undeniably, such a system introduces greater complexity in terms of technologies, knowledge and socio-cultural aspects. Companies are often unprepared to deal with innovation issues, because they lack knowledge and competences and they are not culturally prepared for the relative novelties, but especially because they lack the necessary technological pre-requisites to develop the appropriate technology stack. From this perspective, different models of maturity have been developed, both in academic and technical environments, to support companies in understanding their position within the paradigm of the Industrial Internet. Starting from a quantitative review of the maturity models designed in the general literature, this article develops a qualitative review of the models applied in Industry 4.0, characterising all relevant models and proposing future perspectives to improve existing models and develop new ones

A Conceptual Model for Deploying E-Service in SMEs through Capability Building: A Comparative Case Study

This paper proposes a conceptual implementation model for small and medium enterprises (SMEs) to follow as part of their digital transformation. The conceptual model can be translated into a practical step-by-step guide for SMEs to apply during their digital transformation. The model is based on gradually developing industrial capabilities that can influence production processes performance. We employed a comparative case study approach to capture the lessons learned by SMEs in their journey to develop and implement a production digitalization system for deviation management and performance improvement. The model was validated in the cases of study capturing the actual SMEs’ needs. Managerial capabilities of production processes such as monitoring and control demonstrate to influence the performance positively. The proposed model aims for a full digital transformation by following a gradual approach to being resource-efficient and integrating their business needs. This paper is an extension of work originally presented in APMS 2020, IFIP AICT 592

TÜRKİYE'DEKİ İMALAT ŞİRKETLERİNİN ENDÜSTRİ 4.0 OLGUNLUK DÜZEYİNİN BELİRLENMESİ

Amaç: Bu çalışma, Türkiye'de faaliyet gösteren imalat şirketlerinin Endüstri 4.0 olgunluk düzeylerini belirlemeyi amaçlamaktadır. Yöntem: İmalat işletmelerinin Endüstri 4.0 olgunluk düzeyini belirlemek için gelişmekte olan ülkeler perspektifinde geliştirilmiş olan bir ölçek kullanılmıştır. Araştırmanın örneklemi ISO 500/1000 listesinde yer alan ve Endüstri 4.0 araç ve süreçlerini uygulayan büyük ölçekli imalat firmalarının üst ve operasyonel düzey yöneticileri ile mühendis ve teknik uzmanlarından oluşmaktadır. Anket yoluyla toplanan veriler betimleyici istatistikler yoluyla değerlendirilmiştir. Bulgular: Araştırmanın sonuçları, genel olarak işletmelerin Endüstri 4.0 olgunluk düzeyi (3,92/5,00) bakımından "deneyimli" seviyesini tamamlamak üzere olduğunu göstermektedir. Bununla birlikte, işletmelerin örgütsel yönlerinin iyi bir seviyede olduğu, teknolojik (operasyonel) yönlerinin ise geliştirilmesi gereken alanlar olduğu sonucuna ulaşılmıştır. Özgünlük: Endüstri 4.0 olgunluk düzeyini gelişmekte olan ülkeler perspektifinde değerlendiren çok az sayıda çalışma bulunmaktadır. Bu çalışma aynı zamanda, konuyu geniş bir katılım çerçevesinde ve kapsamlı bir şekilde ele alarak, literatüre katkı sağlamaktadır

Assessment of the readiness and maturity for Industry 4.0 adoption in Indian automobile industries

Purpose: This paper addresses the urgent need to comprehensively assess the preparedness of the Indian automobile industry for adopting Industry 4.0 technologies, a critical imperative for sustaining global competitiveness in one of the world's largest and fastest-growing automotive sectors. The study introduces the Maturity Assessment and Readiness for Industry 4.0 in the Indian Automobile Industry (MARI-IA) Scale, offering a novel contribution to the scientific discourse on this vital issue.Literature Review: The existing literature review underscores the scarcity of tailored tools specifically designed to evaluate Industry 4.0 readiness in the distinctive context of the Indian automotive industry. Methodology: To bridge this gap, the paper employs a survey methodology involving 55 participants from 14 diverse organisations, spanning original equipment manufacturers (OEMs), supplier industries, and service centers. The chosen research object is these organisations, strategically selected to represent the spectrum of the industry. Utilising the MARI-IA Scale, the study systematically assesses maturity and readiness across five pivotal dimensions: Vision, Machines, Practices, Products, and People. Results: The findings reveal discernible variations in readiness levels, with OEMs exhibiting the highest preparedness, followed by supplier and service industries. Large-scale industries consistently outperform their medium, small, and micro-scale counterparts, indicating a pronounced scale-dependent disparity. Notably, the 'People' dimension garnered the highest rating, suggesting an existing readiness for skill enhancement initiatives and heightened customer awareness initiatives. In contrast, the 'Vision' dimension is rated the lowest, signalling a pressing need for increased strategic commitment and top management involvement in implementing Industry 4.0 initiatives. Value: The empirical analysis conducted substantiates the relevance and applicability of the MARI-IA Scale in effectively evaluating ndustry 4.0 readiness in the unique context of the Indian automobile industry. Beyond a mere assessment tool, the results of this study carry significant practical implications for stakeholders, offering a roadmap for enhancing Industry 4.0 preparedness and maintaining a competitive edge in the global automotive landscape. This research is a foundational resource for scholars, industry practitioners, and policymakers navigating the dynamic landscape of Industry 4.0 adoption in the Indian automobile sector

Ready, but challenged:: Diffusion and use of artificial intelligence and robotics in Danish firms

This working paper explores the diffusion and effects of artificial intelligence and robotics on work organization and skills formation in Danish private and public companies. The main focus is on how humans and technology interact, the extent to which employees have the skills to engage in this interaction, and the interplay between job content and technology. The main findings are the following: Artificial intelligence is more diffused and diffuses more rapidly than robotics, and this diffusion is uneven across Danish regions; Danish employees are very confident in using artificial intelligence and robotics, but half of the employees lack the necessary skills; skills are to an important extent acquired through on-the-job learning, which are insufficient in the long run; artificial intelligence involves a larger variety of learning than robotics and has a greater impact on tasks and work organization. The working paper con-cludes with recommendations for policy and management. Important recommendations are that there is a need for policy makers to focus on developing new formal education and training and to innovate existing education in order to ready current and future em-ployees for technological change, and that management needs to focus more on continuous development of their human capital. Lifelong learning and strategic human resource management become increasingly important

Digital Transformation Models for the I4.0 Transition: Lessons from the Change Management Literature

The growing diffusion of digital technologies, especially in production systems, is leading to a new industrial paradigm, named Industry 4.0 (I4.0), which involves disruptive changes in the way companies organize production and create value. Organizations willing to seize the opportunities of I4.0 must thus innovate their processes and business models. The challenges that companies must face for the transition towards I4.0 paradigm are not trivial. Several digital transformation models and roadmaps have been lately proposed in the literature to support companies in such a transition. The literature on change management stresses that about 70% of change initiatives—independently of the aim—fail to achieve their goals due to the implementation of transformation programs that are affected by well-known mistakes or neglect some relevant aspects, such as lack of management support, lack of clearly defined and achievable objectives and poor communication. This paper investigates whether and to what extent the existing digital transformation models (DTMs) and roadmaps for I4.0 transition consider the lessons learnt in the field of change management. To this aim, a Systematic Literature Review to identify existing models and roadmaps is carried out. The results obtained by the review are discussed under the lens of the change-management literature. Based on that, the shortcomings and weaknesses of existing DTMs are pinpointed. Extant DTMs mainly focus on digital transformation initiatives carried out in manufacturing companies; they do not cover all the phases of the digital transformation process but rather focus on the definition of the I4.0 vision, strategy and roadmap. Little attention is devoted to the implementation and consolidation of digital change. Change management lessons are considered to a limited extent, based on which, some suggestions for better dealing with digital transformation initiatives are discussed. The paper contributes to advancing knowledge on models and approaches to support organizations in managing digital transformation. The identification of change management activities that a digital transformation initiative should involve as well as the suggestions on how to effectively deal with it can be used by managers to successfully lead the I4.0 transition journey in their organizations

Towards a Framework for Smart Manufacturing adoption in Small and Medium-sized Enterprises

Smart Manufacturing (SM) paradigm adoption can scale production with demand without compromising on the time for order fulfillment. A smart manufacturing system (SMS) is vertically and horizontally connected, and thus it can minimize the chances of miscommunication. Employees in an SME are aware of the operational requirements and their responsibilities. The machine schedules are prepared based on the tasks a machine must perform. Predictive maintenance reduces the downtime of machines. Design software optimizes the product design. Production feasibility is checked with the help of simulation. The concepts of product life cycle management are considered for waste reduction. Employee safety, and ergonomics, identifying new business opportunities and markets, focus on employee education and skill enhancement are some of the other advantages of SM paradigm adoption. This dissertation develops an SM paradigm adoption framework for manufacturing SMEs by employing the instrumental research approach. The first step in the framework identified the technical aspects of SM, and this step was followed by identifying the research gaps in the suggested methods (in literature) and managerial aspects for adopting SM paradigm. The technical and the managerial aspects were integrated into a toolkit for manufacturing SMEs. This toolkit contains seven modular toolboxes that can be installed in five levels, depending on an SME’s readiness towards SM. The framework proposed in this dissertation focuses on how an SME’s readiness can be assessed and based on its present readiness what tools and practices the SMEs need to have to realize their tailored vision of SM. The framework was validated with the help of two SMEs cases that have recently adopted SM practices