Data on the current state of modular systems in a highly dynamic environment: Empirical analyses in the manufacturing industry and automotive industry of Germany

Today, many companies develop modular systems to realise considerable product differentiation and variation while simultaneously reducing costs through economies of scale [1]. Designing these modular systems to be lasting and robust in a highly dynamic environment [2], avoiding subsequent modification cost [3,4] and staying innovative over the product lifecycle is crucial for sustainable success in an increasingly competitive market [5]. Two closely related surveys were carried out on the initial situation described above. The first survey deals with the major conflict between planning reliability and flexibility with regard to future boundary conditions that the described challenges lead to. The data presented in this article on the first survey was collected from German companies, mainly from the automotive industry, developing and manufacturing complex products using modular systems. Other represented companies operate in the machine and plant construction industry. The survey comprises the answers of 39 participants, gathered via online questionnaire. The 17 questions of the survey are divided into two topics: characteristics of the participants, and the problem description of modular systems in highly dynamic environments and the management thereof. The second survey deals with the anticipation of innovations in the design of modular systems and the selection of the right choice from a variety of possible innovations to be considered. The data presented in this article on the second survey was collected from German automotive manufacturers, which develop and manufacture complex products using modular systems. The survey comprises the answers of 501 participants, gathered via online questionnaire. The 14 questions of the survey are divided into two topics: characteristics of the participants, and the problem description of modular systems and the management thereof. The data obtained allows the identification of existing deficits and dedicated research on solutions. (c) 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).