Alexander Beckers’s research while affiliated with RWTH Aachen University and other places

The cost optimized manufacturing of components represents a central success factor for manufacturing companies. For this purpose, the required final state characteristics of components must be manufactured at the lowest possible efforts. These efforts depend on the companies’ targets and may include the costs of the whole manufacture as well as environmental impacts caused by the manufacturing processes. Each manufacturing process of a process sequence has an influence on both, the final state characteristics of the component and the efforts, so that an improvement of individual processes in a process sequence does not have to lead to the technical and economical (global) optimum. To take this challenge (reaching global optimum) into account, a systematic procedure to combine different models of single manufacturing processes to cross-process models under consideration of the individual model uncertainties and their effects on cross-process models is presented. These cross-process models predict the final state characteristics of a component considering all manufacturing processes of the process sequence. For validation, the systematic approach is applied to a manufacturing process sequence for the manufacturing of indexable inserts.

Agile product development is increasingly finding its way into the development of physical products. The subsequent transfer of a planned and still unstable manufacturing process into stable series production after the design freeze is the goal of ramp-up production, but confronts manufacturing companies with different challenges. A currently high level of changes to the product geometry and the planned manufacturing sequence due to not achieved requirements in late phases of the ramp-up production (Residual Development Efforts—RDE) results in time-consuming and cost-intensive changes to the product and manufacturing sequence, which leads to failure to achieve ramp-up targets. The goal of current research is therefore to increase the agility of ramp-ups and to integrate the ramp-up production into the phase of agile product development. This offers the potential to use the increased dynamics of the product development process and the knowledge already generated for the validation and stabilization of the manufacturing process. However, due to the integration of ramp-up production into product development, there are additional far-reaching effects of product and technology uncertainties prevalent in agile product development on the design of agile ramp-up production. Additional uncertainties regarding the product geometry due to non-finalized designs and the resulting uncertainties regarding the probability of use and achievement of the requirements of the manufacturing technologies initially result in additional residual development efforts. Furthermore, the interactions between the manufacturing technologies in the manufacturing sequence are thus subject to additional uncertainties, which also leads to increased RDEs. To meet this challenge, it is necessary to analyze prevailing uncertainties and predict their impact on potential changes in agile ramp-up production. Therefore, a methodology is presented, which enables the analysis of product and technology uncertainties and thus the identification of product and process-related changes (RDE) in agile ramp-up production.

When manufacturing products, it becomes increasingly important to consider ecological factors in addition to conventional key performance indicators such as manufacturing costs, time or quality. The greatest leverage for creating the most sustainable form of product manufacture is in the early stages of technology planning, because emissions can be avoided in the long term through the selection of sustainable technologies. However, there are methods that allow ecological factors to be taken into account during technology planning to supplement the usual key performance indicators, but the level of detail and the applicability are not yet sufficient. In order to support decision makers in the planning and evaluation of technology chains, this paper develops a methodology that supports technology chain selection. For this purpose, an economic-ecological key performance indicator was developed which combines manufacturing costs, material flow costs and environmental impacts determined through life cycle assessment to enable a holistic view.

As a consequence of the increasing digitalization of production, the availability of data from individual manufacturing processes and components is rising continuously. Digitalization affects various levels of production, such as the design of manufacturing processes, technology planning, quality monitoring, or logistics control. The contribution of this paper is to present the foundations for digitalized manufacturing process sequences and to develop data-based models and methods for the design of economically and ecologically optimized process sequences. For this purpose, a procedure for cross-process life cycle assessment was developed and carried out in order to evaluate the various ecological effects resulting from manufacturing and, in particular, different process designs. This ecological evaluation was combined with the evaluation of economic efficiency in order to provide an integrated evaluation as the basis for the design of manufacturing process sequences. In addition, the effects of the individual manufacturing process designs or process parameters on component quality were analyzed and an approach was derived for determining cross-process dependencies. The basis for these developments is a process sequence for the manufacture of pinion shafts used in electric car gearboxes. This digitalized process sequence consists of the processes soft cutting, gear hobbing, case-hardening, cylindrical grinding, and gear grinding, and over 100 components were manufactured with various process designs. This enabled an extensive amount of process and quality data to be collected throughout the process sequence. The application of the developed methods to the aforementioned process sequence underlines the high potential for the optimization of the target parameters quality, economy and ecology through cross-process analyses of digitalized manufacturing process sequences. Finally, an outlook on further developments regarding the digitalization of manufacturing process sequences is given.

The biological transformation is a growing part of current research in manufacturing and enables new possibilities in the development of innovative products. Modular functional assemblies based on biological building blocks potentially enable efficient and economical functionalization of component surfaces. Surface functionalization covers a range of industries and applications with high economic and technological potential and societal relevance. In dentistry, inflammation of the gums near the implant (periimplant infection) is one of the most common complications after implant implantation. The infections are mainly due to bacterial contamination or bacterial colonization at the implant. Biohybrid coatings based on modular functional assemblies represent an innovative solution for surface functionalization to prevent these periimplant infections. However, in addition to the advantages of modular functional assemblies, there are various challenges for the establishment of functional assemblies in series production. These pose new requirements for the manufacturing technology. The aim of interdisciplinary collaboration between biotechnology, soft matter nanotechnology, polymer chemistry, and production engineering is to provide implant surfaces (using titanium dental implants as an example) with an innovative biohybrid coating in combination with microstructuring. The coating prevents the bacterial colonization of the implant while the microstructure increases the robustness and longevity of the coating. The challenges in manufacturing these micro-structures of surfaces, the generation of biohybrid coatings as well as an outlook on the innovative use of functionalized surfaces are described in this paper.

Manufacturing companies are increasingly confronted with the challenge of adapting components that are already established on the market. As a result, the existing manufacturing process sequences of the corresponding components must also be adapted. Due to the complex technical interdependencies of manufacturing process sequences, adaptations potentially cause change propagation. The change propagation must be considered to ensure the component’s functionality and to enable the selection of the most economical adaptation for the established manufacturing process sequence to implement the required component change. As a contribution to considering change propagation in manufacturing process sequences, a methodology for the deterministic and cost-efficient change propagation analysis is introduced. A case study from medical technology is presented to supplement the explanation of the methodology’s steps and to validate its applicability.

Durch die frühzeitige Ausschussidentifikation und anschließendes Aussteuern von Ausschuss aus der Fertigung ist es möglich, die Herstellkosten zu senken, da die Kosten folgender Prozesse eingespart werden. Eine Möglichkeit zur Ausschussidentifikation stellen Prognosemodelle dar. In diesem Beitrag wird ein Vorgehen zur Ableitung potenzieller Prognosecheckpoints innerhalb von Prozessfolgen vorgestellt. Außerdem wird ein Vorgehen zur Berechnung des Kostensenkungspotenzials zur Bewertung des Einsatzes von Prognosemodellen zur Ausschussidentifikation eingeführt.

Manufacturing companies have to design their manufacturing process sequences so that the product requirements are fulfilled cost-efficiently. It is important that process sequences are designed holistically and that the technological and economic relationships between individual processes are taken into account. It is particularly important to consider these relationships in serial production, because technology experts often design manufacturing processes one process at a time. While the different processes are linked at higher planning levels, the relationships between the manufacturing processes are insufficiently considered. At the design phase, the economic potential of cross-process optimization could be tapped into but remains unused. An approach for the design of economically-optimized manufacturing process sequences is presented in this paper. It describes how technological relationships in a process sequence can be modeled using cross-process models. The approach includes a newly developed model which can be used to economically evaluate process sequences. Within this model, process parameter-dependent variables of the individual manufacturing processes and temporal as well as technological relationships between the processes are considered in order to optimize manufacturing process sequences. A case study shows the potential of cross-process optimization.

Manufacturing companies are more frequently confronted with short-term disruptions due to increasing manufacturing complexity. These disruptions lead to additional costs due to e.g. downtimes. Technological reaction potentials resulting from the adaptation of process parameters are currently neglected when reacting to disruptions. Moreover, technological interrelations between the manufacturing processes are not sufficiently examined. Thus, cost saving potentials are not fully utilized. Therefore, an adaptive reaction is necessary to exploit these potentials. In this paper, three challenges in the adaptive design of manufacturing process sequences in case of short-term disruptions are presented. Furthermore, a concept for overcoming these challenges is outlined.

The adaptation of established products and their components is a crucial process for companies to react to changing environments. To realize a component change, the corresponding manufacture must also be adapted. Often, a specific component change can be realized through alternative Manufacturing Changes, which must be specified and evaluated in relation to one other. A systematic approach to a timely and cost-efficient specification and evaluation of alternative Manufacturing Changes is therefore presented in this paper. The approach is based on an iterative information acquisition process, which generates the input for the specification and evaluation of Manufacturing Changes.