METHOD FOR REFERENCE-BASED MANUFACTURING COST ESTIMATION – EVALUATION STUDY USING A PROTOTYPE

Within product development, manufacturing cost estimation provides a sound basis for design and management decisions. This secures companies profitability, but the effort is high and deep knowledge at the interface of design, manufacturing and costs is needed. These issues can be eased with automation enabled by semantic technologies. Therefore, the authors developed a method for reference-based manufacturing cost estimation and created a prototype. This research evaluates the method and the prototype. Observation, interview and questionnaire were conducted with ten experienced cost engineers at a large German manufacturing company. Based on its results, the study shows the methods contribution to lower estimation effort, while the impact on transparency and the knowledge base was only partly verified. The method steps show different automation potential, so an incremental automation should be considered. Even though semantic technologies show high potential for identifying reference system elements in this study, the limiting factor for automation in manufacturing cost estimation remains the low availability of product and manufacturing information and missing knowledge of its connection within product development

Knowledge graph for manufacturing cost estimation of gear shafts - a case study on the availability of product and manufacturing information in practice

Growing cost pressure forces companies to actively manage their product costs to secure profitability. Here, manufacturing cost estimation within product development estimates manufacturing and material costs. As most products are developed in generations, needed product and manufacturing information can origin from reference system elements (RSE), for example similar components of prior product generations. Problematically, this product and manufacturing information as well as the knowledge of its interrelation is often stored in an unstructured way, document based or at least not machine-readable. This makes manufacturing cost estimation an effortful, time consuming and mainly manual activity with low traceability, where a wide manufacturing knowledge is required. Trends in production, like new manufacturing processes and production systems further increase the need for manufacturing information and knowledge. Knowledge graphs as semantic technologies can improve the findability and reusability of reference system elements and enable automatic information processing. Within this research, cost estimation of research and development of a large automotive supplier was used as research environment. Guided by the model of PGE an ontology for the manufacturing cost estimation domain was developed. Then, a knowledge graph was instantiated based on product and manufacturing information from gear shafts of electric axles. A case study was carried out to evaluate process-specific cycle time calculation as exemplary use case of the knowledge graph. Process-specific cycle times are generally effortful estimated based on detailed manufacturing information and then used together with machine hourly rates to estimate manufacturing costs. Here, the structured and machine-readable manufacturing information of identified reference system elements is extracted from the knowledge graph to reduce the effort, increase the traceability and enable future automation. The case study shows exemplary, how a knowledge graph can support manufacturing cost estimation of gear shafts where product and manufacturing information is automatically identified using reference system elements

Product-Production-CoDesign: An Approach on Integrated Product and Production Engineering Across Generations and Life Cycles

Shorter product life cycles and high product variance nowadays require efficient engineering of products and production systems. Hereby a further challenge is that costs over the entire life cycle of the product and production system are defined early in the process. Existing approaches in literature and practice such as simultaneous engineering and design for manufacturing incorporate aspects of production into product engineering. However, these approaches leave potential for increasing efficiency unused because knowledge from past generations of products, production systems, and business models is not stored and reused in a formalized way and future generations are not considered in the respective current engineering process. This article proposes an approach for integrated product and production engineering across generations and life cycles of products and production systems. This includes the consideration of related business models to successfully establish the products on the market as well as the anticipation of future product and production system characteristics. The presented approach can reduce both development and manufacturing costs as well as time to market and opens the vast technological potential for product design to achieve additional customer benefits. Three case studies elaborate on aspects of the proposed approach and present its benefits