Planning Machine Activity Between Manufacturing Operations: Maintaining Accuracy While Reducing Energy Consumption

There has recently been an increased emphasis on reducing energy consumption in manufacturing. This is largely because of fluctuations in energy costs causing uncertainty. The increased competition between manufacturers means that even a slight change in energy consumption can have implications on their profit margin or competitiveness of quote. Furthermore, there is a drive from policy-makers to audit the environmental impact of manufactured goods from cradle-to-grave. The understanding, and potential reduction of machine tool energy consumption has therefore received significant interest as they require large amounts of energy to perform either subtractive or additive manufacturing tasks. One area that has received relatively little interest, yet could harness great potential, is reducing energy consumption by optimally planning machine activities while the machine is not in operation. The intuitive option is to turn off all non-essential energy-consuming processes. However, manufacturing processes such as milling often release large amounts of heat into the machine's structure causing deformation, which results in deviation of the machine tool's actual cutting position from that which was commanded, a phenomenon known as thermal deformation. A rapid change in temperature can increase the deformation, which can deteriorate the machine's manufacturing capability, potentially producing scrap parts with the associated commercial and environmental repercussions. It is therefore necessary to consider the relationship between energy consumption, thermal deformation, machining accuracy and time, when planning the machine's activity when idle, or about to resume machining. In this paper, we investigate the exploitability of automated planning techniques for planning machine activities between subtractive manufacturing operations, while being sufficiently broad to be extended to additive processes. The aim is to reduce energy consumption but maintain machine accuracy. Specifically, a novel domain model is presented where the machine's energy consumption, thermal stability, and their relationship to the overall machine's accuracy is encoded. Experimental analysis then demonstrates the effectiveness of the proposed approach using a case study which considers real-world dat

Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles

Internationalization of markets and climate change introduce multifaceted challenges for modern supply chain (SC) management in the today's digitalisation era. On the other hand, Automated Guided Vehicle (AGV) systems have reached an age of maturity that allows for their utilization towards tackling dynamic market conditions and aligning SC management focus with sustainability considerations. However, extant research only myopically tackles the sustainability potential of AGVs, focusing more on addressing network optimization problems and less on developing integrated and systematic methodological approaches for promoting economic, environmental and social sustainability. To that end, the present study provides a critical taxonomy of key decisions for facilitating the adoption of AGV systems into SC design and planning, as these are mapped on the relevant strategic, tactical and operational levels of the natural hierarchy. We then propose the Sustainable Supply Chain Cube (S2C2), a conceptual tool that integrates sustainable SC management with the proposed hierarchical decision-making framework for AGVs. Market opportunities and the potential of integrating AGVs into a SC context with the use of the S2C2 tool are further discussed

An Edge-Cloud based Reference Architecture to support cognitive solutions in Process Industry

Process Industry is one of the leading sectors of the world economy, characterized however by intense environmental impact, and very high-energy consumption. Despite a traditional low innovation pace in PI, in the recent years a strong push at worldwide level towards the dual objective of improving the efficiency of plants and the quality of products, significantly reducing the consumption of electricity and CO2 emissions has taken momentum. Digital Technologies (namely Smart Embedded Systems, IoT, Data, AI and Edge-to-Cloud Technologies) are enabling drivers for a Twin Digital-Green Transition, as well as foundations for human centric, safe, comfortable and inclusive workplaces. Currently, digital sensors in plants produce a large amount of data, which in most cases constitutes just a potential and not a real value for Process Industry, often locked-in in close proprietary systems and seldomly exploited. Digital technologies, with process modelling-simulation via digital twins, can build a bridge between the physical and the virtual worlds, bringing innovation with great efficiency and drastic reduction of waste. In accordance with the guidelines of Industrie 4.0 this work proposes a modular and scalable Reference Architecture, based on open source software, which can be implemented both in brownfield and greenfield scenarios. The ability to distribute processing between the edge, where the data have been created, and the cloud, where the greatest computational resources are available, facilitates the development of integrated digital solutions with cognitive capabilities. The reference architecture is being validated in the three pilot plants, paving the way to the development of integrated planning solutions, with scheduling and control of the plants, optimizing the efficiency and reliability of the supply chain, and balancing energy efficiency

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Perspectives of Integrated “Next Industrial Revolution” Clusters in Poland and Siberia

Rozdział z: Functioning of the Local Production Systems in Central and Eastern European Countries and Siberia. Case Studies and Comparative Studies, ed. Mariusz E. Sokołowicz.The paper presents the mapping of potential next industrial revolution clusters in Poland and Siberia. Deindustrialization of the cities and struggles with its consequences are one of the fundamental economic problems in current global economy. Some hope to find an answer to that problem is associated with the idea of next industrial revolution and reindustrialization initiatives. In the paper, projects aimed at developing next industrial revolution clusters are analyzed. The objective of the research was to examine new industrial revolution paradigm as a platform for establishing university-based trans-border industry clusters in Poland and Siberia47 and to raise awareness of next industry revolution initiatives.Monograph financed under a contract of execution of the international scientific project within 7th Framework Programme of the European Union, co-financed by Polish Ministry of Science and Higher Education (title: “Functioning of the Local Production Systems in the Conditions of Economic Crisis (Comparative Analysis and Benchmarking for the EU and Beyond”)). Monografia sfinansowana w oparciu o umowę o wykonanie projektu między narodowego w ramach 7. Programu Ramowego UE, współfinansowanego ze środków Ministerstwa Nauki i Szkolnictwa Wyższego (tytuł projektu: „Funkcjonowanie lokalnych systemów produkcyjnych w warunkach kryzysu gospodarczego (analiza porównawcza i benchmarking w wybranych krajach UE oraz krajach trzecich”))

A Consumer-Centric Open Innovation Framework for Food and Packaging Manufacturing

This article has been archived following written permission from IGI Global.Closed innovation approaches have been employed for many years in the food industry. But, this sector recently perceives its end-user to be wary of radically new products and changes in consumption patterns. However, new product development involves not only the product itself but also the entire manufacturing and distribution network. In this paper, we present a new ICT based framework that embraces open innovation to place customers in the product development loop but at the same time assesses and eventually coordinates the entire manufacturing and supply chain. The aim is to design new food products that consumers will buy and at the same time ensure that these products will reach the consumer in time and at adequate quantity. On the product development side, our framework enables new food products that offer an integrated sensory experience of food and packaging, which encompass customization, healthy eating, and sustainability

Implementation of industry 4.0 in the development of the space industry

Treball Final de Grau en Administració d'Empreses. Codi: AE1049. Curs 2022/2023The deployment of Industry 4.0, which is defined by the integration of sophisticated technology and data-driven processes, has transformed several industries, allowing for higher productivity, efficiency, and flexibility. The space industry is one that has been heavily impacted by Industry 4.0. Driven by technical developments and the desire to explore beyond Earth's borders, the space industry has recognized the potential of Industry 4.0 to improve its operations and push the boundaries of space exploration even further. Space exploration is an enthralling and necessary pursuit that feeds human curiosity while pushing the limits of knowledge and technical innovation. It provides a once-in-alifetime opportunity to explore the universe's mysteries, generating awe and amazement in individuals of all ages. Furthermore, there are various scientific discoveries and technological advances that emerge because of space travel. Fascinating statistics underscore its significance: Over 2,700 exoplanets have been confirmed by NASA's Kepler mission alone, opening new frontiers in the search for extra-terrestrial life, while the International Space Station has hosted more than 240 astronauts from 19 countries, fostering international collaboration and expanding our understanding of human adaptation to space

Nonterrestrial utilization of materials: Automated space manufacturing facility

Four areas related to the nonterrestrial use of materials are included: (1) material resources needed for feedstock in an orbital manufacturing facility, (2) required initial components of a nonterrestrial manufacturing facility, (3) growth and productive capability of such a facility, and (4) automation and robotics requirements of the facility