Logistics

The trend toward digitization o ers considerable potential; this is particularly true in supply chain management (SCM). However, not every technology is suitable for every company and its processes. This article presents a structured approach that supports companies in the selection process. The approach consists of several phases: Starting with the identi cation of business goals and ending with the selection of those technologies that seem most promising. Its applicability was tested in a research project at a logistics service provider. It is easily transferable to a concrete decision-making situation.

Maritime container transport is the backbone of international trade and supply and distribution processes in global manufacturing networks. However, digital support of container transportation related processes is still insu cient. This article shows how a digital platform can facilitate the digital interaction between industry and logistics stakeholders. Using the quotation process as an example, it describes how the platform can support transactions between shippers and transport service providers. Use of the digital platform increases process transparency, reduces duplication of work and reduces the time required to carry out the processes.

The automation of informational logistics processes is already one of the core challenges of manufacturing firms on their way to autonomous logistics systems. It is quite realistic that the majority of informational logistics processes will be running autonomously by the end of this decade. However, the path to this goal is still uncertain. Therefore, this article aims at defining the evolutionary stages of autonomy of logistics processes with the involvement of industry experts, describing prerequisites for reaching individual stages and discussing challenges along the way. In addition, the most important informational logistics processes with high autonomization potential are identified and an estimate is made of when the autonomy levels can be expected to be reached industry-wide.

Intense global competition, shorter product life cycles and an increasing number of variants require flexible and adaptable, but at the same time economical production and logistics systems. This requires constant replanning of factories and logistics systems. Value-adding processes are being outsourced to contract logistics providers. Contract logistics planners must respond to tenders as quickly as possible and develop a proposal with an initial planning concept and a cost estimation. Despite standardization efforts in planning, the knowledge is often only implicit at the planners. This article describes the need for support by an AI-based assistance system during the planning process and how a digital platform for such an assistance system should look like.

With increasing availability of data, the use of machine learning to optimize supply chains becomes attractive, as the accuracy of data analysis can be increased and simultaneously the effort can be reduced. Based on the SCOR model, exemplary approaches are described as a guidance and suitable machine learning methods are presented.

Procurement has the task of providing an organization with required but not self-produced goods. Due to the collapse of global supply chains during the SARS-COV2 pandemic, procurement faced major challenges. Goods that were actually easily available on global markets became critical bottlenecks. It turned out that additive manufacturing can mitigate these bottlenecks. For example, medical spare parts were produced using additive manufacturing. This article examines how additive manufacturing is changing the procurement risk of materials. A comparison is made between traditional and additive supply possibilities based on a survey. The result is a combined procurement strategy, which ensures an improved availability of critical goods.

Due to COVID-19 the production lines of the German automotive manufacturers were stopped for an average of 30 days. Even allegations of exhaust manipulation, the required structural change in the direction of electro mobility as well as stricter CO2 regulations are representatives for risks that impact automotive value chains. In order to encounter such risks in an entrepreneurial manner, cooperative, integrative and analytical skills are required, which are brought together in a mature risk management model. While automotive manufacturers and suppliers are in the scientific and public focus of such risks less attention is paid to the risk management of directly affected contract logistics service providers in this industry. In this article a risk management model for contract logistics service providers in the automotive sector is developed that leads to elaborated risk mitigation strategies. A differentiation of risks should take place on three levels by not only company-internal ...