Enterprises looking to be competitive are constantly looking for a continuous increase in productivity, quality, and level of services. With the development of the industry 4.0 concept, manufacturers are more confident about the new advantages of automation and systems integration. Lean management is a well-developed and empirically proven managerial strategy. Combining lean and industry 4.0 practices seems to be a necessary evolutionary step to further raise the level of operational excellence. This study applied the main path analysis method to explore the development trend of lean management in the academic field. First, this study adopted the Scopus database to collect relevant papers, then analyzed their overall development trajectory by using Main Path 437 software, and used the g-index and h-index to identify more influential journals. Next, this study clustered the papers with similar topics into several groups, and then used Wordle software to present the keywords of each grou... [more]

The incursion of disruptive technologies, such as the Internet of Things, information technologies, cloud computing, digitalization and artificial intelligence, into current production processes has led to a new global industrial revolution called Industry 4.0 or Manufacturing 4.0. This new revolution proposes digitization from one end of the value chain to the other by integrating physical assets into systems and networks linked to a series of technologies to create value. Industry 4.0 has far-reaching implications for production systems and engineering education, especially in the training of mechatronic engineers. In order to face the new challenges of the transition from manufacturing 3.0 to Industry 4.0 and 5.0, it is necessary to implement innovative educational models that allow the systematic training of engineers. The competency-based education model has ideal characteristics to help mechatronic engineers, especially in the development of specific competencies. This article pr... [more]

The existing research and practices have shown that the coordinated implementation of lean-green manufacturing can have a positive impact on the economic and environmental benefits, which is an effective means to ensure the environmental protection of the production process of manufacturing without damaging their profitability. Within the field of lean-green research, there is still a lack of research to analyze the driving factors for the collaborative implementation of integrated lean and green integration. Although, some scholars and researchers have studied lean and green integration paradigms, their research has mostly focused on lean-green integration practices and their impact on environmental performance and their respective operations. In the context of Industry 4.0, this article investigates the driving forces behind the collaborative integration implementation of a lean-green manufacturing system from the viewpoint of stakeholders. Specifically addressing the issues of corre... [more]

The energy consumption of production processes is increasingly becoming a concern for the industry, driven by the high cost of electricity, the growing concern for the environment and the greenhouse emissions. It is necessary to develop and improve energy efficiency systems, to reduce the ecological footprint and production costs. Thus, in this work, a system is developed capable of extracting and evaluating useful data regarding production metrics and outputs. With the extracted data, machine learning-based models were created to predict the expected energy consumption of an automotive spot welding, proving a clear insight into how the input values can contribute to the energy consumption of each product or machine, but also correlate the real values to the ideal ones and use this information to determine if some process is not working as intended. The method is demonstrated in real-world scenarios with robotic cells that meet Volkswagen and Ford standards. The results are promising,... [more]

Technological advances have shown an accentuated growth trend, which is directly proportional to the quality of life in today’s society. As a result, the business market is becoming increasingly competitive and customers are becoming more demanding, forcing companies to look for new tools and adopt new work methodologies to improve their flexibility, effectiveness and efficiency, ensuring a better response to market needs. In this context, the tools for tracking objects, totally or partially automatic, are considered essential technologies to all kinds of analysis and the treatment of business data, providing several benefits to companies, including waste reduction, identification of bottlenecks, cost reduction, improvement of product quality and the entire flow of business information. A case study of an industrial company specializing in machining, polishing and galvanoplasty of metallic alloys, small size pieces to be incorporated in luxury fashion accessories, is presented. Derived... [more]

The concern of sustainable supplier selection has been raised recently in organizations’ decision making to enhance their competitiveness. Many tools have been developed to support supplier evaluation, yet the factors of Industry 4.0 (I4.0) have been ignored despite their impact on sustainable performance. Hence, this paper aims to include the technology of I4.0 as the criteria to evaluate the competence of suppliers in sustainability. Multiple-criteria decision making (MCDM) has been used to build decision-making systems; thus, this study employed two advanced methods of MCDM, the ordinal priority approach (OPA) and measurement of alternatives and ranking according to compromise solution (MARCOS) in a fuzzy environment. To test the feasibility of the proposal, five manufacturers of Vietnam’s leather and footwear industry were hypothetically assigned. Firstly, the evaluation criteria were weighted by OPA. Then, the ranking of alternatives was determined by fuzzy MARCOS. The results sho... [more]

sp. is a microorganism cultured for producing docosahexaenoic acid (DHA). Genome-scale metabolic modeling (GEM) is a promising technique for describing gen-protein-reactions in cells, but with still limited industrial application due to its complexity and high computation requirements. In this work, we simplified GEM results regarding the relationship between the specific oxygen uptake rate (−rO2), the specific growth rate (µ), and the rate of lipid synthesis (rL) using an evolutionary algorithm for developing a model that can be used by a soft sensor for fermentation monitoring. The soft sensor estimated the concentration of active biomass (X), glutamate (N), lipids (L), and DHA in a Schizochytrium sp. fermentation using the dissolved oxygen tension (DO) and the oxygen mass transfer coefficient (kLa) as online input variables. The soft sensor model described the biomass concentration response of four reported experiments characterized by different kLa values. The average range normali... [more]

Industry 4.0 is the latest technological age, in which recent technological developments are being integrated within industrial systems. Consequently, maintenance management of current industrial manufacturing systems is affected by the emergence of the technologies and features of Industry 4.0. This study aimed to conduct a comprehensive literature review to understand how Industry 4.0 technologies and features affect the various functions of maintenance management systems. The reviewing process was initiated by examining the most recent related literature in three different databases. In total, 54 articles were classified into three research categories. Then, the integration of the main functions and components of the adopted maintenance management model and the Industry 4.0 features and technologies were aligned, focusing on the driving force of predictive maintenance. The analysis focused mainly on the technical aspects of the integration process, including integration concepts and... [more]

Supply chain management is one of the most prominent areas that needs to incorporate sustainability to achieve responsible consumption and production (SDG 11).It has been identified that there are limited studies that have presented the significance of different Industry 4.0 technologies from the perspective of sustainable SCM. The purpose of this study is to discuss the role of Industry 4.0 technologies in the context of sustainable SCM, as well as to identify important areas for future research. The PRISM framework is followed to discuss the role and significance of sustainable SCM and the integration of Industry 4.0-enabling technologies such as the Internet of Things (IoT), cloud computing, big data, artificial intelligence (AI), blockchain, and digital twin for sustainable SCM. The findings of the study reveal that there are limited empirical studies for developing countries and the majority are emphasized in case studies. Additionally, a few studies have focused on operational as... [more]

This paper explains the project’s objectives, identifies the key stakeholders, defines the project manager’s authority and provides a preliminary breakdown of roles and responsibilities. For the project’s future, it acts as a source of authority. This paper’s objective is to record the justifications for starting the project, its goals, limitations, solution instructions and the names of the principal stakeholders. This manuscript is meant to be used as a “Project Management Plan Light” for small and medium-sized projects when it would be uneconomical to prepare an entire collection of documents that make up a project management plan. A global media cloud will be provided and managed by the ABC cloud company inside of a consumer’s current premises. In this paper, the authors explain the end-to-end delivery of cloud and compute services. The article mainly focuses on the delivery of virtual machines (VMs), graphics processing unit (GPUs), cloud storage, transcoding, packaging, 24/7 cust... [more]

The article presents the problems connected with the performance evaluation of a flexible production system in the context of designing and integrating production and logistics subsystems. The goal of the performed analysis was to determine the parameters that have the most significant influence on the productivity of the whole system. The possibilities of using automated machine tools, automatic transport vehicles, as well as automated storage systems were pointed out. Moreover, the exemplary models are described, and the framework of simulation research related to the conceptual design of new production systems are indicated. In order to evaluate the system’s productivity, the use of Overall Equipment Efficiency (OEE) metrics was proposed, which is typically used for stationary resources such as machines. This paper aims to prove the hypothesis that the OEE metric can also be used for transport facilities such as Automated Guided Vehicles (AGVs). The developed models include the para... [more]

Modern industrial units collect large amounts of process data based on which advanced process monitoring algorithms continuously assess the status of operations. As an integral part of the development of such algorithms, a reference dataset representative of normal operating conditions is required to evaluate the stability of the process and, after confirming that it is stable, to calibrate a monitoring procedure, i.e., estimate the reference model and set the control limits for the monitoring statistics. The basic assumption is that all relevant “common causes” of variation appear well represented in this reference dataset (using the terminology adopted by the founding father of process monitoring, Walter A. Shewhart). Otherwise, false alarms will inevitably occur during the implementation of the monitoring scheme. However, we argue and demonstrate in this article, that this assumption is often not met in modern industrial systems. Therefore, we introduce a new approach based on the r... [more]

Sensors and process control systems are essential for process automation and optimization. Many sectors have adapted to the Industry 4.0 paradigm, but copper smelters remain hesitant to implement these technologies without appropriate justification, as many critical functions remain subject to ground operator experience. Recent experiments and industrial trials using radiometric optoelectronic data acquisition, coupled with advanced quantitative methods and expert systems, have successfully distinguished between mineral species in reactive vessels with high classification rates. These experiments demonstrate the increasing potential for the online monitoring of the state of a charge in pyrometallurgical furnaces, allowing data-driven adjustments to critical operational parameters. However, the justification to implement an innovative control system requires a quantitative framework that is conducive to multiphase engineering projects. This paper presents a unified quantitative framewor... [more]

Fruits and vegetables are highly nutritious agricultural produce with tremendous human health benefits. They are also highly perishable and as such are easily susceptible to spoilage, leading to a reduction in quality attributes and induced food loss. Cold chain technologies have over the years been employed to reduce the quality loss of fruits and vegetables from farm to fork. However, a high amount of losses (≈50%) still occur during the packaging, pre-cooling, transportation, and storage of these fresh agricultural produce. This study highlights the current state-of-the-art of various advanced tools employed to reducing the quality loss of fruits and vegetables during the packaging, storage, and transportation cold chain operations, including the application of imaging technology, spectroscopy, multi-sensors, electronic nose, radio frequency identification, printed sensors, acoustic impulse response, and mathematical models. It is shown that computer vision, hyperspectral imaging, m... [more]

The complex data characteristics collected in Industry 4.0 cannot be efficiently handled by classical Six Sigma statistical toolkit based mainly in least squares techniques. This may refrain people from using Six Sigma in these contexts. The incorporation of latent variables-based multivariate statistical techniques such as principal component analysis and partial least squares into the Six Sigma statistical toolkit can help to overcome this problem yielding the Multivariate Six Sigma: a powerful process improvement methodology for Industry 4.0. A multivariate Six Sigma case study based on the batch production of one of the star products at a chemical plant is presented.

The general goals of advanced digitized production in the Industry 4.0 stage of the industrial revolution were presented along with the extended holistic model of Industry 4.0, introduced by the authors, indicating the importance of material design and the selection of appropriate manufacturing technology. The effect of the global lockdown caused by the SARS-CoV-2 virus transmission pandemic was a drastic decrease in production, resulting in a significant decrease in the gross domestic product GDP in all countries, and gigantic problems in health care, including dentistry. Dentists belong to the highest risk group because the doctor works in the patient’s respiratory tract. This paper presents a breakthrough authors solution, implemented by the active SPEC strategy, and aims to eliminate clinical aerosol at the source by negative pressure aspirating bioaerosol at the patient’s mouth line. The comparative benchmarking analysis and its results show that only the proprietary solution with... [more]

The development and application of emerging technologies of Industry 4.0 enable the realization of digital twins (DT), which facilitates the transformation of the manufacturing sector to a more agile and intelligent one. DTs are virtual constructs of physical systems that mirror the behavior and dynamics of such physical systems. A fully developed DT consists of physical components, virtual components, and information communications between the two. Integrated DTs are being applied in various processes and product industries. Although the pharmaceutical industry has evolved recently to adopt Quality-by-Design (QbD) initiatives and is undergoing a paradigm shift of digitalization to embrace Industry 4.0, there has not been a full DT application in pharmaceutical manufacturing. Therefore, there is a critical need to examine the progress of the pharmaceutical industry towards implementing DT solutions. The aim of this narrative literature review is to give an overview of the current statu... [more]

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 importanc... [more]

Numerous organizations are striving to maximize the profit of their businesses by the effective implementation of competitive advantages including cost reduction, quick delivery, and unique high-quality products. Effective production-scheduling techniques are methods that many firms use to attain these competitive advantages. Implementing scheduling techniques in high-mix low-volume (HMLV) manufacturing industries, especially in Industry 4.0 environments, remains a challenge, as the properties of both parts and processes are dynamically changing. As a reaction to these challenges in HMLV Industry 4.0 manufacturing, a newly advanced and effective real-time production-scheduling decision-support system model was developed. The developed model was implemented with the use of robotic process automation (RPA), and it comprises a hybrid of different advanced scheduling techniques obtained as the result of analytical-hierarchy-process (AHP) analysis. The aim of this research was to develop a... [more]

Industry 4.0 (I4.0) represents the Fourth Industrial Revolution in manufacturing, expressing the digital transformation of industrial companies employing emerging technologies. Factories of the future will enjoy hybrid solutions, while quality is the heart of all manufacturing systems regardless of the type of production and products. Quality 4.0 is a branch of I4.0 with the aim of boosting quality by employing smart solutions and intelligent algorithms. There are many conceptual frameworks and models, while the main challenge is to have the experience of Quality 4.0 in action at the workshop level. In this paper, a hybrid model based on a neural network (NN) and expert system (ES) is proposed for dealing with control chart patterns (CCPs). The idea is to have, instead of a passive descriptive model, a smart predictive model to recommend corrective actions. A construction plaster-producing company was used to present and evaluate the advantages of this novel approach, while the result... [more]

The paper is a comprehensive but compact review of the literature on the state of illnesses of the human stomatognathic system, related consequences in the form of dental deficiencies, and the resulting need for prosthetic treatment. Types of prosthetic restorations, including implants, as well as new classes of implantable devices called implant-scaffolds with a porous part integrated with a solid core, as well as biological engineering materials with the use of living cells, have been characterized. A review of works on current trends in the technical development of dental prosthetics aiding, called Dentistry 4.0, analogous to the concept of the highest stage of Industry 4.0 of the industrial revolution, has been presented. Authors’ own augmented holistic model of Industry 4.0 has been developed and presented. The studies on the significance of cone-beam computed tomography (CBCT) in planning prosthetic treatment, as well as in the design and manufacture of prosthetic restorations, h... [more]

The industry is generally preoccupied with the evolution towards Industry 4.0 principles and the associated advantages as cost reduction, respectively safety, availability, and productivity increase. So far, it is not completely clear how to reach these advantages and what their exact representation or impact is. It is necessary for industrial systems, even legacy ones, to assure interoperability in the context of chronologically dispersed and currently functional solutions, respectively; the Open Platform Communications Unified Architecture (OPC UA) protocol is an essential requirement. Then, following data accumulation, the resulting process-aware strategies have to present learning capabilities, pattern identification, and conclusions to increase efficiency or safety. Finally, model-based analysis and decision and control procedures applied in a non-invasive manner over functioning systems close the optimizing loop. Drinking water facilities, as generally the entire water sector, ar... [more]

In this paper, multiclass classification is used to develop a novel approach to enhance failure mode and effects analysis and the generation of risk priority number. This is done by developing four machine learning models using auto machine learning. Failure mode and effects analysis is a technique that is used in industry to identify possible failures that may occur and the effects of these failures on the system. Meanwhile, risk priority number is a numeric value that is calculated by multiplying three associated parameters namely severity, occurrence and detectability. The value of risk priority number determines the next actions to be made. A dataset that includes a one-year registry of 1532 failures with their description, severity, occurrence, and detectability is used to develop four models to predict the values of severity, occurrence, and detectability. Meanwhile, the resulted models are evaluated using 10% of the dataset. Evaluation results show that the proposed models have... [more]

The ability to predict and control the outcome of the sheet metal forming process demands holistic knowledge of the product/process parameter influences and their contribution in shaping the output product quality. Recent improvements in the ability to harvest in-line production data and the increased capability to understand complex process behaviour through computer simulations open up the possibility for new approaches to monitor and control production process performance and output product quality. This research presents an overview of the common process monitoring and control approaches while highlighting their limitations in handling the dynamics of the sheet metal forming process. The current paper envisions the need for a collaborative monitoring and control system for enhancing production process performance. Such a system must incorporate comprehensive knowledge regarding process behaviour and parameter influences in addition to the current-system-state derived using in-line... [more]

Industry 4.0 designates the recent digital revolution in the industrial sector, evolving from the comprehensive networking and automation of all the productive areas. Equipment, machinery, materials and products permit to (i) distinguish dealing out environmental settings and current status via sensors; (ii) join them through fixed software; and (iii) progress production procedures in an exclusive method. Additionally, Industry 4.0 exposes new trials to enterprises, especially small and medium-sized enterprises (SMEs). Firms should advance approaches to (i) achieve chances of innovation and digitalization; (ii) expand their processes; and (iii) define innovative business models. Based on these premises, a well-organized political, legal and infrastructural outline is essential to build up a business having an Industry 4.0 approach. Though bigger firms can get ahead through innovation processes and predicting the potential digitalization risks for their business models, SMEs may be in t... [more]