Dynamics in Logistics

This open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions

Dynamics in Logistics

This open access book highlights the interdisciplinary aspects of logistics research. Featuring empirical, methodological, and practice-oriented articles, it addresses the modelling, planning, optimization and control of processes. Chiefly focusing on supply chains, logistics networks, production systems, and systems and facilities for material flows, the respective contributions combine research on classical supply chain management, digitalized business processes, production engineering, electrical engineering, computer science and mathematical optimization. To celebrate 25 years of interdisciplinary and collaborative research conducted at the Bremen Research Cluster for Dynamics in Logistics (LogDynamics), in this book hand-picked experts currently or formerly affiliated with the Cluster provide retrospectives, present cutting-edge research, and outline future research directions

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Process redesign for effective use of product quality information in meat chains

To fulfil segmented consumer demand and add value, meat processors seek to exploit quality differences in meat products. Availability of product quality information is of key importance for this. We present a case study where an innovative sensor technology that provides estimates of an important meat quality feature is considered. Process design scenarios that differ with respect to sorting complexity, available product quality information, and use of temporary buffers are assessed using a discrete event simulation model. Results indicate that increasing sorting complexity by use of advanced product quality information results in a reduction of processing efficiency. Use of production buffers was found to increase processing flexibility and mitigate negative effects of high sorting complexity. This research illustrates how the use of advanced product quality information in logistics’ decision-making affects sorting performance, processing efficiency, and the optimal processing design, an area that has so far received little attention in literature

Business model optimization plan for S.F. Group's fresh e-commerce business

Nowadays, the market is increasingly fierce, so many companies seek new growth points through business diversification. However, logistics companies have not succeeded in integrating business in the e-commerce industry. In order to answer the failure of logistics enterprises in the field of E-commerce, this paper chooses S.F. BEST as the research object. Case study is conducted on JD.com FRESH and MISSHFRESH to explore their successful experience in business model and the diversity of the industry. After that, we proposed feasible suggestions on the problems existing in S.F. Group. The study of this project found that fresh e-commerce not only needs to provide customers with quality products and delivery services but also needs to establish a good relationship with customers through platforms and channels. However, S.F. Group lacked the ability of platform and channel management, and its market positioning was obviously wrong, so it suffered from business failure and financial losses. Aiming at the shortcomings of S.F. Group's business model in market positioning accuracy and resource utilisation ability, this project proposes improvement suggestions and a development plan. By improving the implementation of the plan, we hope to help S.F. Group reshapes its business model and business operation process, and help the company achieve business diversification and vertical integration.Na actualidade, o mercado está cada vez mais feroz, levando a que muitas empresas procurem novas vias de crescimento através da diversificação dos negócios. No entanto, as companhias de logística não conseguiram desenvolver os seus negócios no sector de comércio electrónico. A fim de dar conta do fracasso das referidas companhias no domínio do comércio electrónico, o presente trabalho tem o S.F. BEST como objecto de investigação. O estudo de caso é conduzido para explorar a experiência bem-sucedida do modelo de negócios e a diversidade do setor. Em seguida, propusemos sugestões viáveis sobre os problemas existentes no S.F. Grupo. O estudo do presente trabalho constatou que o comércio electrónico actual não apenas necessita de oferecer aos clientes produtos de qualidade elevada e prestar serviços de entrega eficaz, mas também precisa de estabelecer um bom relacionamento com os clientes através de várias plataformas e canais. No entanto, o S.F. Grupo não possuía a capacidade de gestão de plataforma e canal, com um posicionamento obviamente errado no mercado, por consequência, sofreu de fracasso nos negócios e perdas financeiras. O presente trabalho propõe sugestões de melhoria e um plano de desenvolvimento, focando nas deficiências do modelo de negócios do S.F. Grupo de negócios acerca da imprecisão de posicionamento no mercado e incapacidade de utilização de recursos. Através de melhorar a implementação do plano, esperamos ajudar o S.F. Grupo na reestruturação do modelo de negócios e do processo de operação de negócios, ajuda a empresa a alcançar a diversificação de negócios e integração vertical

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Total Constraint Management for Improving Construction Work Flow in Liquefied Natural Gas Industry

Australia has benefited and will continue to benefit significantly from Liquefied Natural Gas (LNG) investments underway. Managing these LNG projects is challenging as they become increasingly complex and technologically demanding. The primary goal of this thesis is to develop a Total Constraint Management (TCM) method to improve construction work flow during LNG construction. Five controlled experiments were conducted and results show that successful implementation of TCM can significantly improve construction productivity and reduce schedule overruns

Social media data analytics to improve supply chain management in food industries

© 2017 Elsevier Ltd This paper proposes a big-data analytics-based approach that considers social media (Twitter) data for the identification of supply chain management issues in food industries. In particular, the proposed approach includes text analysis using a support vector machine (SVM) and hierarchical clustering with multiscale bootstrap resampling. The result of this approach included a cluster of words which could inform supply-chain (SC) decision makers about customer feedback and issues in the flow/quality of food products. A case study in the beef supply chain was analysed using the proposed approach, where three weeks of data from Twitter were used