Procedure For Hybrid Process Analysis And Design

Performing business processes are a critical asset for manufacturing companies operating on highly competitive markets. Conventional approaches to business process improvement, however, are vulnerable to subjectivity and high manual efforts in their execution. These challenges can be overcome with recent databased approaches that semi-automate process analysis and design. Those approaches formalize methodical knowledge on weakness detection, measure derivation and performance evaluation for business processes into a performance-related decision support. By enabling the databased automation of these tasks this formalization helps to reduce efforts and subjectivity in process analysis and design. However, practice lacks a procedure for applying this decision support in operative business process improvement. Moreover, this decision support only formalises methodological knowledge. Operative business process improvement in practice additionally requires the consideration of experts' contextual knowledge about the company and the business process itself. This paper presents a hybrid approach for the analysis and design of business processes using a databased decision support. First, existing phase models for business process improvement are consolidated into a reference model. Second, an expert-based assessment is conducted on how decision support extends, modifies or eliminates the conventional tasks of process analysis and design. In the third step, a hybrid phase model for process analysis and design is developed that integrates the formalised methodological knowledge of the decision support and contextual knowledge of experts

Concept For Databased Sales And Resource Planning For Re-Assembly In The Automotive Industry

In linear economy, the growing wealth in the world is linked to a growing resource consumption and greenhouse gas emission. This results in a shortage of primary resources, environmental destruction through resource extraction, and global warming. A high productivity of the manufacturing industry, overcapacities and a decrease in the value of existing products intensify this situation. Circular economy offers resource-efficient value addition by multiple utilization of resources. One challenge in this form of value creation is the duration of reconditioning processes and the lack of product innovation in reconditioned products. To bring products back to the market as quickly as possible, the method of Re-Assembly is introduced and focused in this paper. Re-Assembly can be defined as reconditioning old products into new or higher-valued products, by assembling new or remanufactured parts and components after disassembly. However, manufacturing companies face difficulties in industrialization of such methods. In practice, one of the biggest challenges is the mid- and long term planning of the reconditioning process. Due to uncertainties in the quality and quantity of the returning end-of-life products the resulting reconditioning process is challenging to predict in terms of process time and production costs. To encounter this, this paper presents a concept for sales and resource planning in the context of Re-Assembly. In the first step the uncertainties for the long term production planning and the resulting data requirements are identified. Based on this, a concept for sales and resource planning is presented. The approach is based on the Internet of Production reference framework and includes data from the whole product lifecycle. As the area of application, the automotive industry is chosen as it is the largest manufacturing industry in Germany and already leading in the recording of usage data of their products