Delivery times represent a key factor influencing the competitive advantage, as manufacturing companies strive for timely and reliable deliveries. As companies face multiple challenges involved with meeting established delivery dates, research on the accurate estimation of delivery dates has been source of interest for decades. In recent years, the use of machine learning techniques in the field of production planning and control has unlocked new opportunities, in both academia and industry practice. In fact, with the increased availability of data across various levels of manufacturing companies, machine learning techniques offer the opportunity to gain valuable and accurate insights about production processes. However, machine learning-based approaches for the prediction of delivery dates have not received sufficient attention. Thus, this study aims to investigate the ability of machine learning to predict delivery dates early in the ordering process, and what type of information is required to obtain accurate predictions. Based on the data provided by two separate manufacturing companies, this paper presents a machine learning-based approach for predicting delivery times as soon as a request for an offer is received considering the desired customer delivery date as a feature.

Potential spatio-temporal patterns of renewable energies that take into account international climate protection strategies have been neither analysed nor visualised exactly in terms of their landscape complexity. Furthermore, it is unclear what land uses would be prevalent in new energy landscapes, due to a lack of restrictions, and which social conflicts would be associated with these land use changes. There is no knowledge at all about the extent to which existing land use, which has emerged from a capitalistic order, affects the achievement of a carbon-neutral and socially just society. It is also not clear how far it is possible to identify alternative spatial patterns of sustainable energy transition by altering spatial restrictions concerning renewable energies. For this reason, we want to model and visualise a regional energy landscape that corresponds to the objectives of the UN Climate Conference in terms of its regional greenhouse gas balance in the electricity sector. In this regard, the study provides a detailed analysis of the landscape transformations that would occur in rural spaces if those values which attempt to link energy transition to the Paris Agreement were to prevail. The analyses reveal that a strict orientation of the expansion of renewable energies towards climate protection goals would strongly mechanise rural areas, thus significantly transforming their social patterns.

The design of its distribution logistics has a decisive influence on a company’s logistical costs and performance. They therefore make an essential contribution to corporate success. This article describes a method for analysing the potential of distribution logistics in terms of logistical costs and performance. In contrast to previous procedures of business process re-engineering, this method maps distribution logistics holistically under variable distribution structures. The article is focused on the approach and results of a case study in a multinational manufacturer of propulsion and automation technologies for machine construction and systems engineering. The developed method is distinguished by a high degree of practicality and applicability. It will contribute to a more efficient design of distribution logistics.

This paper summarises the research findings of the HyFlowJobShop research project. The aim of the research project is to combine the organisation structure of the flow principle with the principle of job shop production since traditional organisation structures alone can no longer meet the increased demands for a growing number of variants and shorter amortisation periods for production systems due to shorter product life cycles. The combination of the job shop and flow principle to form hybrid organisation structures is intended to offer producing companies an opportunity to position themselves in the conflict between the required flexibility and the achievement of production logistics targets as well as the resulting costs. To quantify the advantages of hybrid organisation structures, various system configurations are examined as part of a simulation study to identify interdependencies and influencing factors.

Bestehende Verfahren zur Losgrößendimensionierung berücksichtigen die vielfältigen Auswirkungen der Losgrößenwahl nur teilweise, was zu einer wirtschaftlich suboptimalen Losgrößenwahl führt. Der Beitrag stellt bestehende Verfahren vor, zeigt die produktionslogistischen Wirkzusammenhänge ausgehend von der Losgröße auf und skizziert einen praxisorientierten Ansatz zur Losgrößenbestimmung. Bestehende Verfahren zur Losgrößendimensionierung berücksichtigen die vielfältigen Auswirkungen der Losgrößenwahl nur teilweise, was zu einer wirtschaftlich suboptimalen Losgrößenwahl führt. Der Beitrag stellt bestehende Verfahren vor, zeigt die produktionslogistischen Wirkzusammenhänge ausgehend von der Losgröße auf und skizziert einen praxisorientierten Ansatz zur Losgrößenbestimmung. Die Controlling - Zeitschrift für erfolgsorientierte Unternehmenssteuerung liefert Monat für Monat fundierte und anwendungsorientierte Fachbeiträge für das Management sowie das Finanz- und Rechnungswesen in Unternehmen. Klar gegliedert und strukturiert werden für alle Controlling-Bereiche die Faktoren für eine erfolgreiche Unternehmenssteuerung aufgezeigt. Weitere Informationen für Autoren und Abonnenten finden Sie unter www.zeitschrift-controlling.de. Month by month, Controlling - Zeitschrift für erfolgsorientierte Unternehmenssteuerung publishes peer-reviewed, applied research contributions for business management, accounting and reporting. Key elements of succesful corporate controlling are presented in an analytic, well-structured manner. Language: German. For more information for authors and subscribers, see www.zeitschrift-controlling.de.