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Industry 4.0 (I4.0) is an extension to the three stages of industry that reshapes it into a combination of physical and digital worlds. The I4.0 paradigm shift coupled with emerging technologies, such as artificial intelligence (AI), robotics, the internet of things (IoT), autonomous vehicles, and digital twins (DTs), have brought and will continue to bring profound changes that impact entire systems across all industries. Despite I4.0's many advantages, it also brings a host of problems and disruptions. These problems and disruptions must be identified to maximize its potential. Saudi Arabia is undergoing significant transformation as it has initiated several plans to develop the industrial sector and enhance its contribution to the national economy. Despite Saudi Arabia's 2030 vision, the industrial sector has still not fully grasped the breadth and depth of the new revolution due to its novelty. This is particularly true in the cement industry, one of the most vital industries in the region. Due to its many unique systemic complexities, the cement industry has faced numerous challenges due to the lack of a comprehensive framework for mitigating disruptions and leveraging I4.0 benefits. Accordingly, the paper conducts an exploratory study on I4.0 for Saudi Arabian cement companies. Therefore, this paper provides an overview of I4.0 for Saudi Arabia's cement companies. The paper analyzes key findings and proposes a plan–do–check–act (PDCA) framework for I4.0 implementation based on a system thinking approach to guide cement companies to strategically embrace the new phenomenon and maximize their key performance indicators. [ABSTRACT FROM AUTHOR]

In the present industry revolution, operations management teams emphasize implementing an efficient process optimization approach with a suitable strategy for achieving operational excellence on the shop floor. Process optimization is used to enhance productivity by eliminating idle activities and non-value-added activities within limited constraints. Various process optimization approaches are used in operations management on the shop floor, including lean manufacturing, smart manufacturing, kaizen, six sigma, total quality management, and computational intelligence. The present study investigates strategies used to implement the process optimization approach provided in the previous research to eliminate problems encountered in shop floor management. Furthermore, the authors suggest an idea to industry individuals, which is to understand the operational conditions faced in shop floor management. The novelty of the present study lies in the fact that a methodology for implementing a process optimization approach with an efficient strategy has been reported for the first time that eliminates problems faced in shop floor management, including industry 4.0. The authors of the present research strongly believe that this research will help researchers and operations management teams select an appropriate strategy and process optimization approach to improve operational performance on the shop floor within limited constraints. [ABSTRACT FROM AUTHOR]

In industry 4.0, industry individuals implement lean and smart manufacturing to improve shop floor management systems. Shop floor management is used to control operational performance and enhance production within limited constraints. Various shop floor management approaches are used in the present scenario of industry 4.0, and mainly include value stream mapping, total productive maintenance, Internet of Things, artificial intelligence, machine learning, and fuzzy logic. The present research aims to develop an open innovation method to achieve sustainability in shop floor management systems in industry 4.0 by using lean and smart manufacturing concepts. The proposed method has been validated by an enhancement obtained in a real case of the shop floor management system in industry 4.0. The authors are confident that the proposed method would provide sustainability in the shop floor management system within limited constraints in industry 4.0. [ABSTRACT FROM AUTHOR]

Adopting and implementing the Industry 4.0 strategy to increase the overall performance of the organization became one of the main aims of organizations. However, ignoring the linkages between implementing strategic decisions and organizational internal factors/forces can endanger and shrink its performance, competitive advantages, and thus its strategic success. In this context, many companies failed to achieve the expected benefits of adopting the Industry 4.0 strategy. Therefore, the gained advantages of adopting the Industry 4.0 strategy should be sustained through perfect and comprehensive integration between Industry 4.0 concepts and the accompanying upgrades and changes in the organizational internal factors/forces. This will capitalize on organizations' internal strengths and avoid weaknesses or turn them into strengths. In this paper, a conceptual model is proposed to investigate the relation between Industry 4.0 and internal organizational forces and examine their impacts on the sustainable competitive advantages of the organization. In the hypothesized model, three innovation capabilities (i.e., technological, economic, and commercial innovation) have been used to mediate the relation between the internal forces and the sustainable competitive advantages in parallel with Industry 4.0 adoption. The model and the proposed hypotheses have been simulated and tested using partial least squares structural equations modeling software called SmartPLS. The sample size used is 125 responses from different manufacturing fields. The results demonstrate the significant role that the internal organizational forces play in maintaining and sustaining the organization's competitive advantages in combination with Industry 4.0. [ABSTRACT FROM AUTHOR]

Currently, Industry 4.0 is word of mouth, and its implementation has gained increased attention from industrial and academic researchers, entrepreneurs, and service providers all over the world. With Industry 4.0, the integration of facilities and products enables real-time data exchange, and the overall production system becomes self-reliant and intelligent to predict and maintain its operational performance. In this research, the lab-scale implementation of Industry 4.0 is implemented for an automatic yogurt filling production system. A mathematical model for the process optimization of Industry 4.0 was also developed. A real-life problem was solved optimally using linear programming techniques with the objective of maximizing the speed of the conveyor belt. Moreover, the sequencing of processing orders using single-dimensional rules was performed. The effects of changes in the feed rate of the yogurt valve and length of the conveyor belt on the feed rate of the flavor valve, speed of conveyor belt, waiting time, processing times, and the different performance measures were investigated at the end. [ABSTRACT FROM AUTHOR]

Big data analytics (BDA) is one of the main pillars of Industry 4.0. It has become a promising tool for supporting the competitive advantages of firms by enhancing data-driven performance. Meanwhile, the scarcity of resources on a worldwide level has forced firms to consider sustainable-based performance as a critical issue. Additionally, the literature confirms that BDA and innovation can enhance firms' performance, leading to competitive advantage. However, there is a lack of studies that examine whether or not BDA and innovation alone can sustain a firm's competitive advantage. Drawing on previous studies and dynamic capability theory, this study proposes that big data analytics capabilities (BDAC), supported by a high level of data availability (DA), can improve innovation capabilities (IC) and, hence, lead to the development of a sustainable competitive advantage (SCA). This study examines the proposed hypotheses by surveying 117 manufacturing firms and analyzing responses via partial least squares–structural equation modeling (PLS-SEM) statistical software. Findings reveal that BDAC relies significantly on the degree of DA and has a significant role in increasing IC. Furthermore, the analysis confirms that IC has a significant and direct effect on a firm's SCA, while BDAC has no direct effect on SCA. This study provides valuable insights for manufacturing firms to improve their sustainable business performance and theoretical and practical insights into BDA implementation issues in attaining sustainability in processes. [ABSTRACT FROM AUTHOR]

The movement to digitally transform Saudi Arabia in all sectors has already begun under the focused "Vision 2030" programme. Consequently, the task of renovating and standardizing manufacturing and other production industries to compete with global challenges is essential. The fourth industrial revolution (Industry 4.0), triggered by the development of information and communications technologies (ICTs), provides a basis for smart automation using decentralized control and advanced connectivity (e.g., Internet of Things). In the areas where the spirit of Industry 4.0 has been embraced, some industries have already implemented these ideas and yielded gains. Learning the principles of Industry 4.0 and having knowledge of this digital industrial revolution is essential for future engineering graduates. In this paper, a case study on building a learning factory from scratch based on the concept of Industry 4.0 is introduced. The initial achievement of a fully automated production line is presented. In doing so, a system with a smart design having smart control and smart monitoring is developed. [ABSTRACT FROM AUTHOR]

With the advent of modern communication and control strategies, existing industrial enterprises are now being transformed as per Industrial Revolution (IR) 4.0 standards to maximize production rates and monetary gains. To cope with the pace of the modern technological revolution, the Government of Saudi Arabia has launched "Vision 2030". This research article presents the full automation process of an existing production line at the College of Engineering, King Saud University, as per "Vision 2030" guidelines. Initially, a production line was designed to produce flavored yogurt bottles from a user-defined flavor and plain yogurt mixture. The research project was completed in two phases. During phase I, smart sensing, control, and automation equipment were used to minimize human intervention, the so-called semi-automated mode of operation. A bottle-feeding mechanism and robotic arms were later integrated to eliminate human intervention during the second phase. Moreover, during phase II, Node-RED, Telegram Bots, and a Raspberry Pi 4 controller were used to achieve IoT-based monitoring and control as per Industry 4.0 requirements. A comparative performance analysis was conducted between semi-automated and fully automated modes of operation to demonstrate the benefits of the fully automated operational mode. The performance of the fully automated system was found to be superior in comparison with the semi-automated system. [ABSTRACT FROM AUTHOR]

Industry 4.0 allows for greater flexibility in production processes so that products can be customized (i.e., mass customization). Innovative production techniques in an industrial liquid/yogurt filling machine (YFM) improved efficiency in the beverage industry. In this study, we have introduced the second phase designed control architecture of our YFM based on the concepts of industry 4.0 incorporating an NFC platform for improving customer satisfaction. Especially during this pandemic period, wireless technologies have been ubiquitous and pervasive for customized products. The basic components of the YFM have been described. High-level control architecture programmed fully automated filling operations, and the design stage of the development of a PFC-based controller for the YFM is elaborated. For the evaluation of the proposed control system, the operations of the electric/pneumatic input devices and actuators were simulated on FluidSIM-MecLab. The results of the simulation verify the design logic of the PFC-based controller. Comparisons were made between different production types using the developing YFM. A complex learning environment replicating a real production system to understand, learn, and apply modern manufacturing approaches has been developed. Through the creation of this YFM, the academic environment and industrial applications are combined. Consequently, the problem verification is becoming more realistic and more efficient than online (trial and error) automation programming. [ABSTRACT FROM AUTHOR]

The movement to digitally transform Saudi Arabia in all sectors has already begun under the "Vision 2030" program. Consequently, renovating and standardizing production and manufacturing industries to compete with global challenges is essential. The fourth industrial revolution (Industry 4.0) triggered by the development of information and communications technologies (ICT) provides a baseline for smart automation, using decentralized control and smart connectivity (e.g., Internet of Things). Industrial engineering graduates need to have acquaintance with this industrial digital revolution. Several industries where the spirit of Industry 4.0 has been embraced and have already implemented these ideas yielded gains. In this paper, a roadmap containing an academic term course based on the concept of Industry 4.0, which our engineering graduates passed through, is presented. At first, an orientation program to students elaborating on the Industry 4.0 concept, its main pillars, the importance of event-driven execution, and smart product manufacturing techniques. Then, various tasks in developing a learning factory were split and assigned among student groups. Finally, the evaluation of student potential in incorporating the Industry 4.0 concept was analyzed. This methodology led to their professional skill development and promoted students' innovative ideas for the manufacturing sector. [ABSTRACT FROM AUTHOR]

The emergence of Industry 4.0, also referred to as the fourth industrial revolution, has entirely transformed how the industry or business functions and evolves. It can be attributed to its broadening focus on automation, decentralization, system integration, cyber-physical systems, etc. Its implementation promises numerous benefits in terms of higher productivity, greater volatility, better control and streamlining of processes, accelerated enterprise growth, sustainable development, etc. Despite the worldwide recognition and realization of Industry 4.0, its holistic adoption is constrained by the requirements of specific skills among the workforce. The personnel are expected to acquire adaptive thinking, cognitive and computational skills, predominantly in the area of information technology, data analytics, etc. Thus, the universities that laid the foundation for future talents or trends in society have to adapt and modernize the existing programs, facilities, and infrastructure. This reshaping of higher education in consonance with the vision of Industry 4.0 possesses its opportunities and challenges. There are, of course, a multitude of factors involved and they need a reasonable assessment to strategically plan this metamorphosis. Therefore, this work aims to explore and analyze the different factors that influence the progression and enactment of Industry 4.0 in universities for sustainable education. For this purpose, a systematic approach based on a questionnaire as well as a SWOT (strengths (S), weaknesses (W), opportunities (O), and threats (T)) integrated with the analytic hierarchy process (AHP) is adopted. The questionnaires are administered to university employees and students (or stakeholders) to assess their viewpoint, as well as to estimate the priority values for individual factors to be included in SWOT. The AHP is implemented to quantify the different factors in terms of weights using a pairwise comparison matrix. Finally, the SWOT matrix is established depending on the questionnaire assessment and the AHP weights to figure out stakeholders' perspectives, in addition to the needed strategic scheme. The SWOT implementation of this research proposes an aggressive approach for universities, where they must make full use of their strengths to take advantage of the emerging opportunities in Industry 4.0. The results also indicate that there are fundamental requirements for universities in Industry 4.0, including effective financial planning, skilled staff, increased industrial partnerships, advanced infrastructure, revised curricula, and insightful workshops. This investigation undoubtedly underlines the importance of practical expertise and the implementation of digital technologies at the university level to empower novices with the requisite skills and a competitive advantage for Industry 4.0. [ABSTRACT FROM AUTHOR]

In recent decades, production in high-volume/low-variety batches is replaced with low-volume/high-variety production type. This type of production demands excessive flows of both material and information. Recent advances in information and communication technologies (ICT), together with the concept of cyber-psychical system (CPS) enable the concept of Industry 4.0 (I4.0). In this paper, the performance of I4.0 related equipment implementation is presented in iterative assembly line balancing (ALB) process of a gearbox assembly line. Largest candidate rule method through spreadsheet simulation was used for tasks reallocations, with the objective to minimize the cycle time when the number of stations is fixed. Utilization of human analysts using snap back method for manual data gathering process still shown advantage over I4.0 equipment utilization in manual ALB. The assembly process is performed in the learning factory environment, and it is considered as very close to real industry process. The major conclusion is that I4.0 is excellent in process data monitoring and product tracking, but activities to be performed to effectively exploit I4.0 is demanding for task reallocations during the balancing procedure. Nevertheless, future enhancements of I4.0 system are listed to bridge this gap and to increase I4.0 system usefulness in the manual assembly line balancing process. [ABSTRACT FROM AUTHOR]

Lean manufacturing is one of the most popular improvement agents in the pursuit of perfection. However, in today's complex and dynamic manufacturing environments, lean tools are facing an inevitable death. Industry 4.0 can be integrated with lean tools to avoid their end. Therefore, the primary purpose of this paper is to introduce an Industry 4.0-based lean framework called dynamic value stream mapping (DVSM) to digitalize lean manufacturing through the integration of lean tools and Industry 4.0 technologies. DVSM with its powerful features is proposed to be the smart IT platform that can sustain lean tools and keep them alive and effective. This paper specifically tackles the scheduling and dispatching in today's lean manufacturing environments, where the aim of this research is developing a smart lean-based production scheduling and dispatching model to achieve the lean target through optimizing the flow along the VSM and minimizing the manufacturing lead time. The developed model, called the real-time scheduling and dispatching module (RT-SDM), runs on DVSM. The RT-SDM is represented through a mathematical model using mixed integer programming. Part of the testing and verification process, a simplified IT-based software, has been developed and applied on a smart factory lab. [ABSTRACT FROM AUTHOR]

Many advanced product manufacturing approaches have been introduced in the market in recent years. Thus, it is critical to develop modern techniques which can effectively familiarize budding minds with the latest manufacturing procedures. In fact, the contemporary training methods and advanced education practices are crucial to uphold the interest of the new generation as well as to equip them with state-of the art systems. There is a need for innovative ideas and effective methodologies to inculcate the desired competency and prepare students for prospective manufacturing set ups. In the latest Industry 4.0 paradigm, visualization technologies, especially virtual reality, have been emphasized to sustainably train and educate young students. This work presents a technique for utilizing the leading visualization method based on virtual reality in product manufacturing. It aims to acquaint students with the prominent concept of Industry 4.0, the reconfigurable manufacturing system (RMS). The RMS has been a demanding topic for the novice and, most often, amateurs are not able to grasp and interpret it. Therefore, this paper outlines the various steps that can be useful for students in order to anticipate the RMS design, interact with it, understand its operation, and evaluate its performance. [ABSTRACT FROM AUTHOR]

With the development of Industry 4.0 and the emergence of the smart factory concept, the traditional philosophy of manufacturing systems will change. The smart factory introduces changes to the factors and elements of traditional manufacturing systems and incorporates the current requirements of smart systems so that it can compete in the future. An increasing amount of research in both academia and industry is dedicated to transitioning the concept of the smart factory from theory to practice. The purpose of the current research is to highlight the perspectives that shape the smart factory and to suggest approaches and technical support to enable the realization of those perspectives. This paper fills this gap by identifying and analyzing research on smart factories. We suggest a framework to analyze existing research and investigate the elements and features of smart factory systems. [ABSTRACT FROM AUTHOR]