Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

Cultivating sustainable cannabis in the Danish Medicinal Cannabis Pilot Programme : a case study at OC CARE ApS

In my research I explore the Danish Medicinal Cannabis Pilot Programme (Pilot Programme). The study was done with the case of OC Care ApS’ (OC Care) Envision Concept, a legislation-compliant growth facility with a controlled environment, designed to produce sustainable medicinal cannabis. OC Care was chosen as the single case for this study because they are the only licensed company with the aim to produce organic cannabis within the Pilot Programme. OC Care’s Envision Concept is analyzed through an agroecological perspective, by considering the economic, environmental, and social components that together make a system. To understand the context and set the boundaries for the study, the Pilot Programme is analyzed through system thinking methodology. To reach a holistic understanding of the case and its context, data was gathered through multiple sources: participant observation, informal conversations, and semi-structured interviews. Findings indicate that the Pilot Programme has a cautious approach towards legalization, and aims to produce scientific evidence to validate the benefits of medicinal cannabis and regulate its cultivation, processing, and distribution. Due to its pharmaceutical paradigm, hybrid framework, and Denmark’s competitive advantages, Denmark is becoming a leader in the European medicinal cannabis market. To produce organic and sustainable medicinal cannabis OC Care have developed the Envision Concept, a controlled environment cultivation and processing facility, compliant with the European Union’s (EU) Volume 4 EU Guidelines for Good Manufacturing Practice for Medicinal Products for Human and Veterinary Use. The Envision Concept is a system that integrates economic, environmental, and social interests to provide patients with an organic, standardized, and sustainable pharma-grade product.M-A

Upgrading Pathways of Intelligent Manufacturing in China: Transitioning across Technological Paradigms

Intelligent technologies are leading to the next wave of industrial revolution in manufacturing. In developed economies, firms are embracing these advanced technologies following a sequential upgrading strategy—from digital manufacturing to smart manufacturing (digital-networked), and then to new-generation intelligent manufacturing paradigms. However, Chinese firms face a different scenario. On the one hand, they have diverse technological bases that vary from low-end electrified machinery to leading-edge digital-network technologies; thus, they may not follow an identical upgrading pathway. On the other hand, Chinese firms aim to rapidly catch up and transition from technology followers to probable frontrunners; thus, the turbulences in the transitioning phase may trigger a precious opportunity for leapfrogging, if Chinese manufacturers can swiftly acquire domain expertise through the adoption of intelligent manufacturing technologies. This study addresses the following question by conducting multiple case studies: Can Chinese firms upgrade intelligent manufacturing through different pathways than the sequential one followed in developed economies? The data sources include semi-structured interviews and archival data. This study finds that Chinese manufacturing firms have a variety of pathways to transition across the three technological paradigms of intelligent manufacturing in non-consecutive ways. This finding implies that Chinese firms may strategize their own upgrading pathways toward intelligent manufacturing according to their capabilities and industrial specifics; furthermore, this finding can be extended to other catching-up economies. This paper provides a strategic roadmap as an explanatory guide to manufacturing firms, policymakers, and investors.This research is supported by the National Natural Science Foundation of China (91646102, L1824039, L1724034, L1624045, and L1524015), the project of China’s Ministry of Education “Humanities and Social Sciences (Engineering and Technology Talent Cultivation)” (16JDGC011), CAE Advisory Project “Research on the strategy of Manufacturing Power towards 2035” (2019-ZD-9), the National Science and Technology Major Project “High-end Numerical Control and Fundamental Manufacturing Equipment” (2016ZX04005002), Beijing Natural Science Foundation Project (9182013), the Chinese Academy of Engineering’s China Knowledge Center for Engineering Sciences an Technology Project (CKCEST-2019-2-13, CKCEST-2018-1-13, CKCEST-2017-1-10, and CKCEST-2015-4-2), the UK–China Industry Academia Partnership Programme (UK-CIAPP\260), as well as the Volvo-supported Green Economy and Sustainable Development Tsinghua University (20153000181) and Tsinghua Initiative Research Project (2016THZW)

A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics

Industry 4.0 concepts and technologies ensure the ongoing development of micro- and macro-economic entities by focusing on the principles of interconnectivity, digitalization, and automation. In this context, artificial intelligence is seen as one of the major enablers for Smart Logistics and Smart Production initiatives. This paper systematically analyzes the scientific literature on artificial intelligence, machine learning, and deep learning in the context of Smart Logistics management in industrial enterprises. Furthermore, based on the results of the systematic literature review, the authors present a conceptual framework, which provides fruitful implications based on recent research findings and insights to be used for directing and starting future research initiatives in the field of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in Smart Logistics

A new human-centric factory model

The traditional manufacturing concept puts tasks at the center of the production system and the workers’ role is rather passive. However, the workplaces of the future will be worker-centric instead of task-centric, and the role of the workers is expected to increase, leading to an optimization of the production performance. In this manner, it is of paramount importance to define new social sustainable workplaces where the human dimension is a key cornerstone, highlighting the requirements for shifting from a traditional task-centric production to a worker centric production. The idea of this study is to design the workplaces of the future and to understand how the worker's role will change in the next years, focusing on the workers’ perspective to create workplaces that fit to their needs. The study therefore highlights a new human-centric factory model and provides a taxonomy of the aspects to be considered in designing these worker-centric factories of the future. The EU-Funded Man-Made Project is used for the development and validation of the concepts of the research work utilizing case studies in the transportation and white-goods industries

Sines industrial and logistics zones: FDI determinants applied to Sines and its peers

The goal of this case study is to identify the FDI location determinants according to the most recent scientific studies and match those location determinants with the ones that can be found at Sines’s Cluster. Firstly I had to define the main competitor countries and in order to keep things simple I only chose six countries: Germany, Netherlands, Spain, Poland, Egypt and Morocco. The countries Spain, Egypt and Morocco are direct competitors for FDI attraction while Germany and Netherlands compete in terms of containers transhipment. The information was gathered by searching on database like OCDE, World Bank and Bloomberg but also by talking with AICEP Global Parques and with Port Authority of Sines. From my theoretical research reducing total costs of the supply chain is crucial nowadays therefore Portugal can win from this since has a better relation between labour costs and qualified labour than Spain. Morocco has a poor infrastructure reducing its attractiveness but the labour is low qualified and cheap therefore might be good for labour intensive industries. Regarding the Eastern Europe countries, after analysing the location determinants they are inferior to Portugal. Germany and Netherland are better than the rest of the countries analysed in almost all aspects, except in labour costs. Portuguese Government should try to lower Tax in order to increase the competitiveness of the cluster versus the Eastern Europe clusters and also should work to attract a logistics third party in order to increase the efficiency of the cluster.O objectivo deste caso de estudo do Cluster de Sines é identificar os determinantes de localização de acordo com a pesquisa mais recente e comparar com os determinantes de localização que o cluster de Sines tem. Em primeiro lugar foi necessário definir os países que competem directamente sendo restringidos a seis: Alemanha, Holanda, Espanha, Polónia, Egipto e Marrocos. Os países Espanha, Egipto e Marrocos são os principais concorrentes de Portugal em relação à atracção de investimento directo estrangeiro já a Alemanha e Holanda são concorrentes em relação ao transporte de contentores (transhipment). A informação foi recolhida através da pesquisa nas bases de dados da OCDE, Banco Mundial e Bloomberg mas também através de entrevistas com a AICEP Global Parques e Autoridade Portuária de Sines. Com base na pesquisa teórica reduzir os custos totais da cadeia de abastecimento é fundamental e Portugal pode ganhar com isso pois tem melhor relação custo da mão-de-obra versus qualidade da mão-de-obra que a Espanha. Em relação a Marrocos, as infra-estruturas são fracas o que reduz a atractividade deste mas a mão-de-obra é barata e pouco qualificada o que é ideal para indústrias intensivas em mão-de-obra. Quanto aos países do leste da Europa tem uma atractividade mais baixa que Portugal quando considerados todos os determinantes de localização. Já a Alemanha e Holanda são melhores que os restantes Países analisados em todos os aspectos expecto nos custos de mão-de-obra. O Governo Português precisa de reduzir os impostos para que o Cluster de Sines consiga rivalizar com os restantes clusters concorrentes e também devia debruçar-se sobre a necessidade de um operador logístico no cluster de forma a aumentar a eficiência do mesmo

日本の電力部門における炭素・水・エネルギー・ネクサスと交通部門のエネルギー転換のシナリオ分析

Tohoku University博士（環境科学）thesi