Hermann Kloberdanz

An Approach to Classify Methods to Control Uncertainty in Load-Carrying Structures

Today, a wide variety of methods to deal with uncertainty in load-carrying system exists. Thereby, uncertainty may result from not or only partially determined process properties. The present article proposes a classification of methods to control uncertainty in load-carrying systems from different disciplines within mechanical engineering. Therefore, several methods were collected, analysed and systematically classified concerning their characteristic into the proposed classification. First, the classification differs between degrees of uncertainty according to the model of uncertainty developed in the Collaborative Research Centre CRC 805. Second, the classification differs between the aim of the respective method to descriptive methods, evaluative methods or methods to design a system considering uncertainty. The classification should allow choosing appropriate methods during product and process development and thus to control uncertainty in a systematic and holistic approach.

Modellierung von Unsicherheit in der Produktentwicklung

Fur die erfolgreiche Entwicklung von Produkten sind typischerweise eine Vielzahl von Einflussfaktoren zu beruksichtigen. Aufgrund von Unsicherheiten, z.B. fehlenden Informationen oder schwankende Einflussgrosen im Produktlebenslauf, ist eine detaillierte Analyse jedoch haufig schwierig. In diesem Beitrag wird deswegen die Wahrscheinlichkeits- mit der Moglichkeitstheorie verglichen, um die Anwendbarkeit beider Theorien fur eine quantitative Analyse von Unsicherheiten im Rahmen der Produktentwicklung zu untersuchen. Am Beispiel eines Euler-Knickstabes werden die Einschrankungen einer statistischen Analyse sowie die Vorteile der Berechnung einer unscharfen, kritischen Knicklast aufgezeigt. Das Ziel ist eine geeignete Beschreibung relevanter Unsicherheiten als Grundlage fur die Entwicklung robuster Produkte. Die vorgestellten Betrachtungen sind Teilergebnisse des Sonderforschungsbereichs 805 „Beherrschung von Unsicherheit in lasttragenden Systemen des Maschinenbaus“ der Deutschen Forschungsgemeinschaft an der Technischen Universitat (TU) Darmstadt.

An Assignment of Methods to Analyze Uncertainty in Different Stages of the Development Process

During its life cycle, each engineering product goes through different stages of planning, production and usage. Uncertainties occur in all of these phases. As defined, uncertainties in technical systems are present as far as product and process properties are not determined and deviations of these properties arise. They result either from imperfect information about output values of production processes (regarding product properties) or in terms of diverging uses of the products. Especially within the product development process, the occurring uncertainties have to be taken into account. During the early design stages, decisions that have a variously strong impact on the future product are made. Moreover, the knowledge about a future product is still low so that neither the expected processes nor the product’s properties are known. For this reason, well-known methods of probabilistic uncertainty analysis are not sufficient. They cannot be applied until the product is completely defined. A comprehensive uncertainly analysis in the product development process can be executed in an integrated process model with the Uncertainly Mode and Effects Analysis Methodology (UMEA) [1]. The underlying model of uncertainly is the basis for a comprehensive and consistent classification of uncertainly, a distinction comparable to concepts such as reliability, availability, error or risk. The model to analyze uncertainty has been exercised using the example of the product development process according to Pahl/Beitz [2]. It enables the assignment of suitable methods for the classification of uncertainty at different stages in the design process and thus different levels of abstraction. Based on this model, the quantitative methods of the probability theory are complemented by qualitative concepts such as risk analysis methods, for example, FailureMode and Effects Analysis (FMEA), Event Tree Analysis (ETA), or Hazard and Operability (HAZOP). The assignment of methods offers the possibility to analyze the classified uncertainties in the different phases of the product development process.Copyright

Uncertainty in Product Modelling within the Development Process

This paper gives an overview about how to locate uncertainty in product modelling within the development process. Therefore, the process of product modelling is systematized with the help of characteristics of product models and typical working steps to develop a product model. Based on that, it is possible to distinguish between product modelling uncertainty, mathematic modelling uncertainty, parameter uncertainty, simulation uncertainty and product model uncertainty.

An Approach to Using Elemental Interfaces to Assess Design Clarity

The authors propose a method to assess the clarity of a design on working principle level. To do so, the Contact and Channel Model is used in an adapted form to differentiate elemental interfaces based on their geometry and function. This classification is used to derive a generic catalogue of elemental interfaces. A product can be represented through a combination of these interfaces and working structures in between. The design clarity can then be assessed through generic information stored in the catalogue. The authors propose a procedure model to implement this method and show exemplarily its applicability. Additionally, main design parameters that strongly affect a product’s behavior can be identified with help of the generic catalogue for every elemental interface. Finally, further steps regarding variability in design parameters are discussed.

Uncertainty Scaling – Motivation, Method and Example Application to Aload Carrying Structure

Scaling methods allow the estimation of the impact of changes in individual parameters on system performance. In the technical context, physical similarity is the focus. This paper demonstrates the extension of scaling methods to include uncertainty scaling. The advantages of using scaling uncertainty for the development of scaled products and the contribution of extended scaling methods to the analysis and assessment of uncertainty are illustrated. Uncertainty scaling based on dimensional analysis and complete similarity is derived. The potential of this method is demonstrated using a load carrying structure - a buckling beam.