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In process optimization, a process is adjusted so as to optimize a set of parameters while meeting constraints, with the objective to either minimize the total processing time or maximize the throughput. This article focused on the process optimization of a fully automated yogurt and flavor-filling machine developed based on the industrial revolution 4.0 concept. Mathematical models were developed for minimizing the total processing time or maximizing the throughput of an Industry 4.0-based yogurt filling system with two different machine settings called Case-I and Case-II. In Case-I, the yogurt and flavors are filled at two distinct points while Case-II considers the filling of yogurt and flavors at a single point. The models were tested with real data and the results revealed that Case-II is faster than Case-I in processing a set of customer orders. The results were used as inputs for the single-dimension rules to check which one results in more intended outputs. Additionally, different performance measures were considered and the one with most importance to the management was selected. [ABSTRACT FROM AUTHOR]

This study undertakes the line balancing problem while allocating reconfigurable machines to different workstations. A multi-objective model is used to analyze the position of workstations, assignment of configurations to workstations, and operation scheduling in a reconfigurable manufacturing environment. A model is presented that comprises the objectives of the Total Time (TT), the Line Efficiency Index (LEI), and the Customer Satisfaction Index (CSI). The objective is to minimize the completion time and maximize the efficiency of a production line. The proposed model combines the Simple Line Balancing Problems Type 2 and Type E in the form of SLBP-2E. The presented problems are addressed by using a heuristic solution approach due to non-polynomial hard formulation. The heuristic approach is designed to assess different solutions based on no repositioning, separate repositioning of workstations and configuration, and simultaneous repositioning of workstations and configurations. A detailed assessment is presented regarding the efficiency as well as the effectiveness of proposed approaches. Finally, conclusions and future research avenues are outlined. [ABSTRACT FROM AUTHOR]

Remanufacturing is considered as the most preferable recovery option. The objective of this paper was to identify the environmental inventory of a remanufacturing initiative. A window-mount air conditioner (AC) was selected as a case study to verify the environmental benefits of remanufacturing a product characterized by high energy consumption during its life cycle phases. A life cycle approach was followed. The research aims to provide a reference case in the remanufacturing of products characterized by energy intensive use, of which an AC is one of them. The assessment was conducted with the guidance of the ISO 14044-2006 life cycle assessment (LCA). The significance of this study lies in the fact that it provides an authentic example wherein the environmental inventory of the remanufacturing process is identified and documented. It can be used in further studies to compare the environmental burden of remanufacturing processes to the process of manufacturing a new AC. The developed life cycle analysis can be utilized to help AC manufacturers make decisions about the overall environmental performance of their products if it goes through the remanufacturing cycle. [ABSTRACT FROM AUTHOR]

Production-line sensors are essential for synchronisation and execution of the correct workflow in a manufacturing process. Usually, sensor faults lead to serious delays, or even the complete termination of the manufacturing process, to carry out maintenance. Thus, sensor faults compromise the reliability of the manufacturing system and disturb the production schedule. This study proposes a multiple-sensor fault detection and isolation scheme for manufacturing series production lines. The proposed scheme adopts a global-redundancy method, using a digital camera and an ad-hoc video processing algorithm to detect and isolate faulty sensors. The main objective of this research is to preserve continuity of the production workflow and solve the problem of production delays and interruptions. Moreover, the scheme provides the possibility of online and post-process system maintenance. Further, the collected information on sensor false alarm rates can be used for a reliability analysis of the production line. The proposed scheme was tested using a laboratory production line model. The results show that the proposed scheme achieves the established objectives and improves the reliability of the manufacturing process. [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]

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]