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Institut / FIR-Bereiche
The quarrying industry, which largely consists of less digitized SMEs, is an integral part of the German economy. More than 95% of the primary raw materials produced are used by the domestic construction industry. Quarrying companies operate demand-oriented with short planning horizons at several locations simultaneously. Due to the low level of digitization and the reluctance to share data, untapped efficiency potential in data-based demand forecasting and capacity planning arises. The situation is aggravated by the fact that SMEs have a heterogeneous mobile machinery so as not to become dependent on individual suppliers, and that transport distances of over 50 kilometers are uneconomical due to high transport costs and low material values. Within the research project PROmining a data-centric platform which improves demand forecast accuracy and multi-site capacity utilization is developed. One of the core functionalities of this platform is an industry-specific demand forecasting model. Against this background, this paper presents a methodology for establishing this forecasting model. To this end, expected demands of secondary industry sectors will be analyzed to improve mid-term volume-forecasting accuracy for the local quarrying industry. The data-centric platform will connect demand forecasting data with relevant key performance indicators of multi-site asset utilization. Following this methodology, operational planning horizons can be extended while significantly improving overall production efficiency. Thus, quarrying businesses are enabled to respond to fluctuating demand volumes effectively and can increase their personnel and machine utilization across multiple quarry sites.
Ziel des Forschungsprojekts ‚PROmining‘ war die unternehmensneutrale Konzeptionierung, Entwicklung und Realisierung eines webbasierten Demonstrators zur Verbesserung der Prognosefähigkeit und Erhöhung der Kapazitätsauslastung von KMU in der deutschen Steine- und Erdenindustrie. Mit dem geplanten Demonstrator einer Plattformlösung sollte ein Anreiz für KMU geschaffen werden, die digitale Transformation anzugehen und die interne Datenhaltung zu verbessern. Das Projekt wurde vom FIR e. V. an der RWTH Aachen in Kooperation mit dem Institute of Mineral Resources Engineering der RWTH Aachen durchgeführt.
Digitalization offers companies strategic advantages through the simplification and optimization of business procedures and is an important lever for long-term growth. Numerous industries already benefit from optimized coordination of capacities and resources by integrating digital technologies into business processess. Digital platforms enable, e. g. the demand-based adjustment of asset capacities at peak loads on the basis of data-based forecasts. In particular, small and medium sized enterprises in the German quarrying indsutry have so far been denied access to such technologies due to high investment and operating costs, high implementation efforts and heterogeneous machine fleets. This paper presentes the functions of the data-centric platform demonstrator " PROmining" developed in an AiF research project and validates them using case studies in the industry. The platform demonstrator offers marginally digitalised companies a tool with functions ranging from simple operational data collection, the evaluation of capacity utilization, to scenario development for regional demand, which can be used as a blueprint within their own company. Thus, companies in the quarrying sector are provided with a low-effort entry into the digital transformation and a contributio to long-term competitiveness.
Digitalization offers companies strategic advantages through the
simplification and optimization of business processes and is an
important lever for long-term growth. Numerous industries already
benefit from optimized coordination of capacities and resources by
integrating digital technologies into business processes. Digital platforms enable, e. g., the demand-based adjustment of asset capacities at peak loads on the basis of data-based forecasts. In particular, small and medium-sized enterprises in the German quarrying industry have so far been denied access to such technologies due to high investment and operating costs, high implementation efforts and heterogeneous machine fleets. This paper presents the functions of the data-centric platform demonstrator “PROmining” developed in
an AiF research project and validates them using case studies with
companies in the industry. The platform demonstrator offers marginally digitalised companies a tool with functions ranging from simple
operational data collection, the evaluation of capacity utilization,
to scenario development for regional demand, which can be used
as a blueprint within their own company. Thus, companies in the
quarrying sector are provided with a low-effort entry into the digital
transformation and a contribution to long-term competitiveness.