Constraint-based Scheduling for Paint Shops in the Automotive Supply Industry

Factories in the automotive supply industry paint a large number of items requested by car manufacturing companies on a daily basis. As these factories face numerous constraints and optimization objectives, finding a good schedule becomes a challenging task in practice, and full-time employees are expected to manually create feasible production plans. In this study, we propose novel constraint programming models for a real-life paint shop scheduling problem. We evaluate and compare our models experimentally by performing a series of benchmark experiments using real-life instances in the industry. We also show that the decision variant of the paint shop scheduling problem is NP-complete.

Human-Machine Communication and Crisis Management. An Automotive Industry Case Study

The article presents some results of a larger study of crisis management in the automotive supply industry. This paper studies human - machine communication during organizational crises, an issue that can make the difference between success and failure. The topic is even more challenging in the highly standardized and regulated automotive industry. Using some methodologies taken from social sciences, we analyse the manner in which employees in the automotive supply industry handle unforeseen events. In spite of the increased number of standards and regulations, employees display ambiguous behaviour during unforeseen events, affecting trust in human-machine communication.

Analyzing industry stakeholders using open-source competitive intelligence – a case study in the automotive supply industry

PurposeContinually evolving market structures characterized by high competition and simultaneous coopetition raise the need for the awareness of strategic actions of industry stakeholders and therefore the field of competitive intelligence (CI). Hence, this paper aims to provide a case-based method to enrich and automate the entire CI cycle using open-source data to analyze the industry environment.Design/methodology/approachThe research method is based on design science research and accompanied by a three-year continuous in-depth case study in the automotive supply industry using unstructured, qualitative data to examine the activities of 25 industry stakeholders.FindingsThis paper provides a new holistic method for gaining valuable insights for decision-makers presented through a multiple-layer perspective of the industry development including structural transformation and strategic alignments in functional and cross-sectional areas of the stakeholders.Research limitations/implicationsThe development of a holistic approach using open-source data combines the knowledge-based view and industry economics and allows easy transferability to any other industry.Practical implicationsThe proposed method shows an increase in knowledge for managers to support daily work as well as strategic decision-making. Furthermore, it is proven that even unexperienced CI analysts are empowered to deliver high-quality results.Originality/valueThe paper contributes to the literature and practice of CI by using an approach, which uses unstructured, qualitative data to enrich the entire CI cycle in a business-to-business environment. The case description confirms performance and time improvements of the method and shows the potential of the created insights.