Setup time reduction of an automotive parts assembly line using Lean Tools and Quality Tools

The business world is becoming more competitive. Therefore, it is crucial to increase the flexibility of production by decreasing the time used in the processes of preparing the production lines for new items’ production, reducing changeover and setup times. This paper presents a case study where the main goal is to reduce the setup time of welding robots. Single Minute Exchange of Die (SMED) was implemented, using other tools such as the Spaghetti Diagram, ERCS Analysis (Eliminate, Rearrange, Combine, Simplify), Gemba Walk, Standardized Work, Flowcharts, and Pareto Diagram. The setup time decreased by 36% in the welding robots studied, decreasing the motions by 43% during the changeover process and reducing the time from the categories: “transportation”, “main”, “other”, and “waiting”. In addition to SMED implementation, this study offers an integrated study of several Lean tools and Quality tools to achieve the maximum reduction of changeover and setup times.info:eu-repo/semantics/publishedVersio

Quality 4.0 and Cognitive Engineering Applied to Quality Management Systems: A Framework

In order to create high-quality products, quality engineering must be integrated across the entire product development process. To accomplish the ultimate goal, innovative approaches are required, and a Quality Management System-QMS is imperative to standardize all processes. All business areas depend on people and processes, but quality is especially dependent on them. A QMS can benefit from the application of Quality 4.0—Q4.0 and Cognitive Engineering—CE aspects to reduce the workload and cognitive capacity required from QMS specialists, using these technologies to tackle long-standing quality concerns and to re-optimize to deliver creative solutions. The decision to implement a QMS based on Q4.0 technologies is difficult to take due to the challenge that is to automatize dispersed activities. The purpose of this paper is to develop a framework that aids in the application of a Q4.0 QMS. The relationship between quality management practices and Industry 4.0 technologies that improve quality are deeply studied and connected with CE practices to develop an advanced framework, that makes it easier to overview all the dispersed activities within the manufacturing environment gathered as one, and simplify the application of new technologies to the QMS activities. The proposed framework was developed as result of this study.This work has been supported by the project INDTECH 4.0 (POCI-01-0247-FEDER-026653), co-financed by the PT2020 and COMPETE2020 programs, and the European Union through the European Regional Development Fund (ERDF). FCT.info:eu-repo/semantics/publishedVersio

Lean Tools Selector - A Decision Support System

Small and Medium Enterprises (SMEs) contribute significantly to the economy of any country, but in return, they are limited in their resources. A large part of these companies, when setting out to promote the Lean Manufacturing (LM) have difficulties with the selection and analysis of Lean tools to implement. Eventually, if the improvement actions aren't properly planned, structured or supported by the whole organization then, they end up failing in their implementation. Besides this problem, the literature on LM does not provide enough information about how the selection of Lean tools or practices should be conducted. Therefore, this study presents a decision support system that can help organizations to identify waste and to select the most appropriate tools or Lean practices to implement. It should be noted that, before any implementation of a Lean tool or practice, the organization should take care of knowing its stakeholders, define its system, be informed of the current state of the organization, and identify all the processes that add value to the organization. The correct selection of Lean tools or practices does not ensure the success of the Lean philosophy in any organization, because there are some factors that must be required, namely, the commitment of top management, knowing how to lead and communicate with all employees, being the education and training a crucial point to ensure a good cultural change in the organization.This work was supported in part by Fundação para a Ciência e Tecnologia (FCT) and C-MAST- Centre for Mechanical and Aerospace Science and Technologies, under project UIDB/00151/2020.info:eu-repo/semantics/publishedVersio

The sociodemographic challenge in human-centred production systems – a systematic literature review

industries are currently struggling with ageing workforce in modern production systems associated with industry 4.0. The industrial socio-demographic problem is more and more present as the increas-ing of the ageing population results in the prolongation of the work-ing life and the consecutively in the ageing of the workforce in industries. This paper aims to conduct a systematic literature review on the challenges and concerns of ageing operators, including the physical, cognitive, ergonomic, and well-being conditions of the age-ing workforce in the industry 4.0 environment. The ScienceDirect, Scopus, web of Science and PubMed scientific databases were used to survey the studies and selected using PRiSMA guidelines. This paper was structured and analysed by clusters: Ageing, industry 4.0, Human Factors, and ergonomics. These clusters were developed as research lines: Ageing as the socio-demographic challenge, industry 4.0 as the technological development, Human Factors as the individual charac-teristics of the operator, and ergonomics as the work environment. Thus, human-centric approaches and ideas are discussed with the insights and issues of industry 4.0 technologies, Human Factors, and ergonomics to achieve a sustainable system at the engineering and social level.info:eu-repo/semantics/publishedVersio

Relevant occupational health and safety risks in the Portuguese food processing industry

The Agrifood Industry is the largest Portuguese Industry, constituted mainly by micro, small and medium-sized enterprises (SMEs). It is noted that more than any other type of organization SMEs have their own specificities that make it particularly appropriate to develop tools to facilitate communication and knowledge sharing for employers and workers. To this extent, identifying critical success factors is the key to increase SMEs productivity. Likewise, Occupational Safety and Health (OSH) in SMEs have their own characteristics, which difficult the prevention strategies implementation and aggravate the problematic of work accidents. This study analyses a fieldwork in 60 food processing companies in Portugal, related to the dairy, meat processing, bakery and horticultural subsectors. The analysis of the results allowed to identify that, at the national and regional level, the main failures are concerned with (1) lack of risk assessments regarding occupational noise, lighting, thermal environment and vibrations; (2) safety signaling, the circulation ways are not identified with appropriate safety colors; (3) general lighting, with too many shade areas and finally (4) complementary presence of associated risks to falls at the same level, falling of objects, thermal burns, the use of machines and equipment, fire, mechanical, ergonomic hazards and incorrect body postures. This study assesses the most relevant occupational health and safety risks in the Portuguese food processing industry to contribute to the improvement of OSH management and prevention of work accidents.info:eu-repo/semantics/publishedVersio

Is Industry 5.0 a Human-Centred Approach? A Systematic Review

Industry 5.0 presents itself as a strategy that puts the human factor at the centre of production, where the well-being of the worker is prioritized, as well as more sustainable and resilient production systems. For human centricity, it is necessary to empower human beings and, respectively, industrial operators, to improve their individual skills and competences in collaboration or cooperation with digital technologies. This research’s main purpose and distinguishing point are to determine whether Industry 5.0 is truly human-oriented and how human centricity can be created with Industry 5.0 technologies. For that, this systematic literature review article analyses and clarifies the concepts and ideologies of Industry 5.0 and its respective technologies (Artificial Intelligence, Robotics, Human-robot collaboration, Digitalization), as well as the strategies of human centricity, with the aim of achieving sustainable and resilient systems, especially for the worker.info:eu-repo/semantics/publishedVersio

Modeling Soil Water Content and Reference Evapotranspiration from Climate Data Using Deep Learning Method

In recent years, deep learning algorithms have been successfully applied in the development of decision support systems in various aspects of agriculture, such as yield estimation, crop diseases, weed detection, etc. Agriculture is the largest consumer of freshwater. Due to challenges such as lack of natural resources and climate change, an efficient decision support system for irrigation is crucial. Evapotranspiration and soil water content are the most critical factors in irrigation scheduling. In this paper, the ability of Long Short-Term Memory (LSTM) and Bidirectional LSTM (BLSTM) to model daily reference evapotranspiration and soil water content is investigated. The application of these techniques to predict these parameters was tested for three sites in Portugal. A single-layer BLSTM with 512 nodes was selected. Bayesian optimization was used to determine the hyperparameters, such as learning rate, decay, batch size, and dropout size.The model achieved the values of mean square error values within the range of 0.014 to 0.056 and R2 ranging from 0.96 to 0.98. A Convolutional Neural Network (CNN) model was added to the LSTM to investigate potential performance improvement. Performance dropped in all datasets due to the complexity of the model. The performance of the models was also compared with CNN, traditional machine learning algorithms Support Vector Regression, and Random Forest. LSTM achieved the best performance. Finally, the impact of the loss function on the performance of the proposed models was investigated. The model with the mean square error as loss function performed better than the model with other loss functions.Project Centro-01-0145-FEDER000017-EMaDeS-Energy, Materials, and Sustainable Development, co-funded by the Portugal 2020 Program (PT 2020), within the Regional Operational Program of the Center (CENTRO 2020) and the EU through the European Regional Development Fund (ERDF). Fundação para a Ciência e a Tecnologia (FCT—MCTES) also provided financial support via project UIDB/00151/2020 (C-MAST).info:eu-repo/semantics/publishedVersio

Decision Support System in Dynamic Pricing of Horticultural Products Based on the Quality Decline Due to Bacterial Growth

A decision support system (DSS) was developed to help reduce food waste at traditional food retailers while selling fresh horticultural products, but also to promote food safety and quality. This computational tool includes two major functions: (1) the prediction of the remaining shelf life of fresh horticultural product, namely lettuce, onion, carrot, and cabbage based on its microbial growth status, governed by extrinsic and intrinsic parameters (temperature, water activity and pH, respectively). The remaining shelf life of the studied horticultural products is determined by using the online predictive food microbiology tool— the Combined Database for Predictive Microbiology (Combase). The time to reach the infectious doses of bacteria considered in the study for each of the four horticultural products are predicted; (2) the calculation of the dynamic price of the produce that should be set each day, depending on the predicted end of the marketing period to increase the demand and potential for sale to the final consumer. The proposed dynamic pricing model assumes a linear relation with the remaining shelf life of the analyzed vegetable to set the selling price. The shelf life determined by the DSS for optimal storage conditions is, in general, conservative, ensuring food safety. The automatic dynamic pricing gives new opportunities to small retailers to manage their business, fostering profit and simultaneously contributing to reduce food waste. Thus, this decision support system can contribute to the sustainable value of reducing food waste by providing information to small grocers and retailers on the safety of their perishable status depending on storage conditions and allowing them to suggest a fair price depending on that quality.This study is within the activities of project “PrunusPós—Optimization of processes for the storage, cold conservation, active and/or intelligent packaging and food quality traceability in post-harvested fruit products”, project n. º PDR2020-101-031695, Partnership n.º 87, initiaciative n.º 175, promoted by PDR 2020 and co-funded by EAFRD within Portugal 2020. P.D.G. acknowledges Fundação para a Ciência e a Tecnologia (FCT—MCTES) for its financial support via the project UIDB/00151/2020 (C-MASTinfo:eu-repo/semantics/publishedVersio

Novel Design of Assistive Technologies Based on the Interconnection of Motion Capture and Virtual Reality Systems to Foster Task Performance of the Ageing Workforce

Demographic changes, increasing life expectancy, and increasing healthy life expectancy lead to an increasingly ageing workforce. This condition has a growing impact on the workforce in today’s industries. However, old workers are not a burden for companies and industries. They are a fundamental part of the industrial ecosystem due to the consistency of their human factors, namely their large knowledge, experience, and decision-making ability. For this reason, the ageing workforce must be incorporated and engaged through the introduction of digital age technologies to improve their working conditions and extend their active life. This paper focuses on a novel design of assistive technologies based on the interconnection of motion capture (MoCap) and virtual reality (VR) systems as a driver for the improvement of the task performance of the ageing workforce. We intend to explore how this technological tool can help and enhance the work of the ageing workforce. For this, we study two different areas of application: the training, learning, and communication of the older workers and the ergonomic analysis and workplace design for the ageing operators. In the end, a pilot study is proposed to apply this technology in real work environments.info:eu-repo/semantics/publishedVersio

Environmental Risk Assessment and Management in Industry 4.0: A Review of Technologies and Trends

In recent decades, concern with workers’ health has become a priority in several countries, but statistics still show that it is urgent to perform more actions to prevent accidents and illnesses related to work. Industry 4.0 is a new production paradigm that has brought significant advances in the relationship between man and machine, driving a series of advances in the production process and new challenges in occupational safety and health (OSH). This paper addresses occupational risks, diseases, opportunities, and challenges in Industry 4.0. It also covers Internet-of-Things-related technologies that, by the real-time measurement and analysis of occupational conditions, can be used to create smart solutions to contribute to reducing the number of workplace accidents and for the promotion of healthier and safer workplaces. Proposals involving smart personal protective equipment (smart PPE) and monitoring systems are analyzed, and aspects regarding the use of artificial intelligence and the data privacy concerns are also discussed.info:eu-repo/semantics/publishedVersio