Human Behavior in the Context of Continuous Change - An Exploratory Analysis in a Research and Application Center Industry 4.0

The modern world of work is characterized by discontinuity and innovation. Organizations must adapt to continuous change, which makes it crucial to manage organizational knowledge. Learning and forgetting processes are necessary to react successfully to the changes. On the individual level, this means that individuals have to adapt their behavior, which is often well-learned and routinized. This study aims to take a first step toward a more detailed understanding of human behavior in the context of continuous change. For this purpose, an exploratory analysis was conducted on data collected in a Research and Application Center Industry 4.0. The participants had to deal with the continuous change of routine actions in a simulated production environment, which enabled us to measure their adaptation errors. The occurrence of adaptation errors, their dependency on the type of change, and the behavioral patterns are discussed in detail. Implications for further research are derived

Business and Energy Efficiency in the Age of Industry 4.0: The Hulten, Broweus and Van Dijk Sensory Marketing Model Applied to Spanish Textile Stores during the COVID-19 Crisis

Strategic and tactical factors come into play in shop competitiveness where, in addition to the products sold, other marketing mix variables must also be considered. There are also subjective factors, such as perceptions through the senses. This became even more important when, as a result of the COVID-19 crisis and the forced closure of certain establishments with physical sales, it was necessary to increase profitability and efficiency. The aim of this study was to determine the exact role of sensory marketing in shop efficiency and profitability, based on the guiding principles of technology, innovation, and respect for the environment. We conducted an exploratory and experimental study consisting of the creation of a sensory strategy through the adaptation of the Hulten, Broweus and Van Dijk model on a specific establishment in the current era of Industry 4.0. The results indicate an increase in sales as well as customer satisfaction and happiness after implementing the relevant strategies. The conclusions show that this model is valid and reliable for physical retail establishments, and that these business strategies can significantly contribute to the optimisation of energy resources

Development of a Coordinate Measuring Machine-Based Inspection Planning System for Industry 4.0

Industry 4.0 represents a new paradigm which creates new requirements in the area of manufacturing and manufacturing metrology such as to reduce the cost of product, flexibility, mass customization, quality of product, high level of digitalization, optimization, etc., all of which contribute to smart manufacturing and smart metrology systems. This paper presents a developed inspection planning system based on CMM as support of the smart metrology within Industry 4.0 or manufacturing metrology 4.0 (MM4.0). The system is based on the application of three AI techniques such as engineering ontology (EO), GA and ants colony optimization (ACO). The developed system consists of: the ontological knowledge base; the mathematical model for generating strategy of initial MP; the model of analysis and optimization of workpiece setups and probe configuration; the path simulation model in MatLab, PTC Creo and STEP-NC Machine software, and the model of optimization MP by applying ACO. The advantage of the model is its suitability for monitoring of the measurement process and digitalization of the measurement process planning, simulation carried out and measurement verification based on CMM, reduction of the preparatory measurement time as early as in the inspection planning phase and minimizing human involvement or human errors through intelligent planning, which directly influences increased production efficiency, competitiveness, and productivity of enterprises. The measuring experiment was performed using a machined prismatic workpiece (PW)

Digital Manufacturing as a basis for the development of the Industry 4.0 model

The digital manufacturing (DM) is base for Industry 4.0, that have following dimensions: (i) digital manufacturing based on advanced digital-oriented technologies, (ii) smart products (advanced production mode and new characteristics), and (iii) smart supply - chain (procurement of raw materials and delivery of finished products). Bidirectional exchange of information in collaborative production, using it exchange also for digital platforms of design of the innovative products. This paper presents developed model of Serbian digital factory with selected examples, specifically for the Manufacturing Execution System (MES) area

Development of a Coordinate Measuring Machine-Based Inspection Planning System for Industry 4.0

Industry 4.0 represents a new paradigm which creates new requirements in the area of manufacturing and manufacturing metrology such as to reduce the cost of product, flexibility, mass customization, quality of product, high level of digitalization, optimization, etc., all of which contribute to smart manufacturing and smart metrology systems. This paper presents a developed inspection planning system based on CMM as support of the smart metrology within Industry 4.0 or manufacturing metrology 4.0 (MM4.0). The system is based on the application of three AI techniques such as engineering ontology (EO), GA and ants colony optimization (ACO). The developed system consists of: the ontological knowledge base; the mathematical model for generating strategy of initial MP; the model of analysis and optimization of workpiece setups and probe configuration; the path simulation model in MatLab, PTC Creo and STEP-NC Machine software, and the model of optimization MP by applying ACO. The advantage of the model is its suitability for monitoring of the measurement process and digitalization of the measurement process planning, simulation carried out and measurement verification based on CMM, reduction of the preparatory measurement time as early as in the inspection planning phase and minimizing human involvement or human errors through intelligent planning, which directly influences increased production efficiency, competitiveness, and productivity of enterprises. The measuring experiment was performed using a machined prismatic workpiece (PW)

Digital Manufacturing as a basis for the development of the Industry 4.0 model

The digital manufacturing (DM) is base for Industry 4.0, that have following dimensions: (i) digital manufacturing based on advanced digital-oriented technologies, (ii) smart products (advanced production mode and new characteristics), and (iii) smart supply - chain (procurement of raw materials and delivery of finished products). Bidirectional exchange of information in collaborative production, using it exchange also for digital platforms of design of the innovative products. This paper presents developed model of Serbian digital factory with selected examples, specifically for the Manufacturing Execution System (MES) area

Software Components for Smart Industry Based on Microservices: A Case Study in pH Control Process for the Beverage Industry

[EN] Modern industries require constant adaptation to new trends. Thus, they seek greater flexibility and agility to cope with disruptions, as well as to solve needs or meet the demand for growth. Therefore, smart industrial applications require a lot of flexibility to be able to react more quickly to continuous market changes, offer more personalized products, increase operational efficiency, and achieve optimum operating points that integrate the entire value chain of a process. This requires the capture of new data that are subsequently processed at different levels of the hierarchy of automation processes, with requirements and technologies according to each level. The result is a new challenge related to the addition of new functionalities in the processes and the interoperability between them. This paper proposes a distributed computational component-based framework that integrates communication, computation, and storage resources and real-time capabilities through container technology, microservices, and the publish/subscribe paradigm, as well as contributing to the development and implementation of industrial automation applications by bridging the gap between generic architectures and physical realizations. The main idea is to enable plug-and-play software components, from predefined components with their interrelationships, to achieve industrial applications without losing or degrading the robustness from previous developments. This paper presents the process of design and implementation with the proposed framework through the implementation of a complex pH control process, ranging from the simulation part to its scaling and implementation to an industrial level, showing the plug-and-play assembly from a definition of components with their relationships to the implementation process with the respective technologies involved. The effectiveness of the proposed framework was experimentally verified in a real production process, showing that the results scaled to an industrial scale comply with the simulated design process. A qualitative comparison with traditional industrial implementations, based on the implementation requirements, was carried out. The implementation was developed in the beverage production plant "Punta Delicia", located in Colima, Mexico. Finally, the results showed that the platform provided a high-fidelity design, analysis, and testing environment for cyber information flow and their effect on the physical operation of the pH control.This work has been supported by for research cooperation between Universidad de Colima (Mexico), Universidad Autonoma de Occidente (Colombia), Universitat Politecnica de Valencia (Spain) and the juice production plant Punta Delicia located in Colima, Mexico.Serrano-Magaña, H.; González-Potes, A.; Ibarra-Junquera, V.; Balbastre, P.; Martínez-Castro, D.; Simó Ten, JE. (2021). Software Components for Smart Industry Based on Microservices: A Case Study in pH Control Process for the Beverage Industry. Electronics. 10(7):1-21. https://doi.org/10.3390/electronics1007076312110

Semantic Segmentation to Develop an Indoor Navigation System for an Autonomous Mobile Robot

In this study, a semantic segmentation network is presented to develop an indoor navigation system for a mobile robot. Semantic segmentation can be applied by adopting different techniques, such as a convolutional neural network (CNN). However, in the present work, a residual neural network is implemented by engaging in ResNet-18 transfer learning to distinguish between the floor, which is the navigation free space, and the walls, which are the obstacles. After the learning process, the semantic segmentation floor mask is used to implement indoor navigation and motion calculations for the autonomous mobile robot. This motion calculations are based on how much the estimated path differs from the center vertical line. The highest point is used to move the motors toward that direction. In this way, the robot can move in a real scenario by avoiding different obstacles. Finally, the results are collected by analyzing the motor duty cycle and the neural network execution time to review the robot’s performance. Moreover, a different net comparison is made to determine other architectures’ reaction times and accuracy values.This research was financed by the plant of Mercedes-Benz Vitoria through the PIF program to develop an intelligent production. Moreover, The Regional Development Agency of the Basque Country (SPRI) is gratefully acknowledged for their economic support through the research project “Motor de Accionamiento para Robot Guiado Automáticamente”, KK-2019/00099, Programa ELKARTEK

Towards Supply Chain Visibility Using Internet of Things:A Dyadic Analysis Review

The Internet of Things (IoT) and its benefits and challenges are the most emergent research topics among academics and practitioners. With supply chains (SCs) gaining rapid complexity, having high supply chain visibility (SCV) would help companies ease the processes and reduce complexity by improving inaccuracies. Extant literature has given attention to the organisation’s capability to collect and evaluate information to balance between strategy and goals. The majority of studies focus on investigating IoT’s impact on different areas such as sustainability, organisational structure, lean manufacturing, product development, and strategic management. However, research investigating the relationships and impact of IoT on SCV is minimal. This study closes this gap using a structured literature review to critically analyse existing literature to synthesise the use of IoT applications in SCs to gain visibility, and the SC. We found key IoT technologies that help SCs gain visibility, and seven benefits and three key challenges of these technologies. We also found the concept of Supply 4.0 that grasps the element of Industry 4.0 within the SC context. This paper contributes by combining IoT application synthesis, enablers, and challenges in SCV by highlighting key IoT technologies used in the SCs to gain visibility. Finally, the authors propose an empirical research agenda to address the identified gaps