Joining Constraint Satisfaction Problems and Configurable CAD Product Models: A Step-by-Step Implementation Guide

In configuration design, the task is to compose a system out of a set of predefined, modu-lar building blocks assembled by defined interfaces. Product configuration systems, both with or without integration of geometric models, implement reasoning techniques to model and explore the resulting solution spaces. Among others, the formulation of constraint satisfaction problems (CSP) is state of the art and the informational background in many proprietary configuration engine software packages. Basically, configuration design tasks can also be implemented in modern computer aided design (CAD) systems as these contain different techniques for knowledge-based product modeling but literature reports only little about detailed application examples, best practices or training materials. This article aims at bridging this gap and presents a step-by-step implementation guide for CSP-based CAD configurators for combinatorial designs with the example of Autodesk Inventor

Modeling the Portfolio of Capabilities for Product Variant Creation and Assessment

Choice navigation, solution space development and robust process design are the three mass customization key competences. The first and second are often mapped into product configuration or design automation systems and aim at specifying or co-designing a suitable product variant. Robust process design targets at managing a well-known but flexible supply network. As part of this, the portfolio of capabilities describes limitations to the solution space and is a valuable source of knowledge containing general design guidelines and specific manufacturing restrictions, like NC travelling distances, as well as availabilities of whole production processes. This article contributes a modeling approach that bridges solutions space development and modeling the portfolio of capabilities. Therefore, a knowledge-based engineering system is extended by a capability model of according production machines that allows to automatically check new product variants against the portfolio of capabilities and to estimate setup efforts and expenses of process changes

Agent collaboration in a multi-agent-system for analysis and optimization of mechanical engineering parts

In mechanical engineering, designers have to review a designed artefact iteratively with different domain experts, e.g. from manufacturing, to avoid later changes and find a robust, optimized design. To support the designer, knowledge-based engineering offers a set of approaches and techniques that formalize and implement engineering knowledge into generic product models or decision support systems. An implementation which satisfies especially the concurrent nature of today's design processes and allow for multi-objective decision-making is multi-agent systems. Such systems consist of entities that are capable of autonomous action, interact intelligently with their environment, communicate and collaborate. In this paper, such a multi-agent system is discussed as extension for a computer-aided design software where the agents take the role of domain experts, like e.g. manufacturing technologists and make suggestions for the optimization of the design of mechanical engineering parts. A focal point is set on the collaboration concept of the single agents. Therefore, the paper proposes the use of an action-item-list as central information and knowledge sharing platform. © 2020 The Authors. Published by Elsevier B.V

Product-Service-Systems : What and why Developers can learn from Mass Customization

Despite their very similar objectives, delimitations or associations between the two business types of mass customization and providers of product-service-systems (PSS) cannot be found in literature. In the following article, both business types are compared with each other and mapped into a common businesstypological framework, the product-process-baseline-change matrix. Following that, the development of PSS is characterized especially with regard to the (re-)configurability of PSS over the life-cycle. Since product configuration is one of the key tools in the development and the customer co-design process in mass customization, its application to PSS is evaluated and present PSS-configuration approaches are discussed

Making design decisions under uncertainties: probabilistic reasoning and robust product design

Making design decisions is characterized by a high degree of uncertainty, especially in the early phase of the product development process, when little information is known, while the decisions made have an impact on the entire product life cycle. Therefore, the goal of complexity management is to reduce uncertainty in order to minimize or avoid the need for design changes in a late phase of product development or in the use phase. With our approach we model the uncertainties with probabilistic reasoning in a Bayesian decision network explicitly, as the uncertainties are directly attached to parts of the design artifact′s model. By modeling the incomplete information expressed by unobserved variables in the Bayesian network in terms of probabilities, as well as the variation of product properties or parameters, a conclusion about the robustness of the product can be made. The application example of a rotary valve from engineering design shows that the decision network can support the engineer in decision-making under uncertainty. Furthermore, a contribution to knowledge formalization in the development project is made

Design Automation Case Study : Modular Locating Fixture

Design automation systems often mimic human designers and implement routine design activities. Beside this, the idea of such knowledge-based engineering is to support developers in the analysis and syntheses of complex engineering artifacts. An instance of this is product configuration. A central aspect of knowledge-based engineering is its ability to draw conclusions about the design context. For this inference, different reasoning techniques have been proposed. One uses constraint satisfaction problems as model-based approach. In the present contribution, the authors report about a case-study about the implementation of a constraint-based configuration system with onboard resources of a computer aided design system on the example of a locating fixture

Using Axiomatic Design for the Development of Product Configuration Systems

In order to meet a wide range of customer requirements in product development, a high degree of individualization is necessary today, which can be achieved with product configuration systems. Knowledge-based CAD models are a useful tool for implementing such configurators, but they are significantly more complex to develop than conventional parametric CAD models. To master this complexity, this article examines the use of the axiomatic design approach for the development of a configurator for a skip loader. In combination with the parameter space matrix, an application-oriented methodology is derived which is suitable for the development of similar configuration systems

Application of system dynamics for holistic product-service system development

In order to develop Product Service Systems (PSS), a holistic view on the system and a coequal development of service and product parts is necessary. Particularly for the beginning of the development of PSS, existing approaches show lacks and start with vague defined initial phases. This leads to inadequate methodological support for the consistent design of the overall system and simultaneous elaboration of the requirements down to the parameters of individual components. Therefore, a procedure is required that completely maps the PSS and enables detailed development for relevant individual areas, taking into account existing constraints. At the beginning of the development a model is necessary, which first defines the system boundaries of the PSS and maps the performance and control flows of the system. In addition, the integration of further actors into the PSS must be made possible. This paper presents an approach that uses System Dynamics (SD) to design a PSS. With this approach, the representation of the system is initially possible at a high level of abstraction, whereby the representation can be further refined and detailed. Parallel to this, a preliminary design for planning and controlling media flows can be carried out from the first system representation and further detailed parallel to the system representation. An essential advantage is that the detailing can also only be carried out for individual areas, which can be displayed in sub-models, but can also be reintegrated into the overall representation. The sub-models can be implemented function-specifically on the basis of resources and competencies of individual actors. For system-relevant areas, planning and design can be concretized in the sub-models (which can be realized by products as well as services) down to the lowest hierarchy level. This can take place up to the definition of individual physical component parameters and has thus up to the phase of the elaboration effects on the development of the parts. In return, the effects of changes in system-relevant parameters on the overall system can also be examined. For the PSS, a model is built in which system-determining functions and principles are represented and developed. The model is constructed in such a way that non-system-determining functions and principles are defined as variables or black boxes. Requirements and parameters are derived from this system development. These are used for the further development steps in the development process. Depending on whether it concerns system-relevant areas or not, the entry into the development process takes place later in the elaboration phase (e.g. in the area of detailed design) or partly earlier in the concept phase (e.g. function development). It is also possible to enter an early phase in the development process of the individual parts, accompanied by already defined functions, sub-functions or parameters that must not be changed in the course of development. With this approach a holistic development of the system with all product and service parts as well as their connections and dependencies is possible

Process Chain-Oriented Design Evaluation of Multi-Material Components by Knowledge-Based Engineering

The design of components suitable for manufacturing requires the application of knowledge about the manufacturing process chain with which the component is to be manufactured. This article presents an assistance system for decision support in the context of design for manufacturing. The assistance system includes explicit manufacturing process chain knowledge and has an inference engine that can automatically evaluate the manufacturability of a component design based on a given manufacturing process chain and resolve emerging manufacturing conflicts by making adjustments on the component or resource side. A link with a CAD system additionally enables the three-dimensional representation of derived manufacturing stages and manufacturing resources. Within the assistance system, a manufacturing process chain is understood as a configurable design object and is implemented via a constraint satisfaction problem. Furthermore, the required abstraction of manufacturing processes within finite domains can be reduced to the extent that necessary modeling resolution is achieved by incorporating empirical or simulative surrogate models into the CSP. The assistance system was conceptually validated on a tailored forming process chain for the production of a multimaterial shaft and provides added value, as valuable manufacturing information for component designs is automatically derived and made available in explicit form during the component development

Constraint Solver for a Fixture Design: Results of a Student Case Study

For teaching students the skills of programming and usage of knowledge-based engineering systems, we conduct student projects in a lecture in which they independently represent a configuration solution space and resolve it using a constraint solver. For this purpose, the lecture is conducted in a flipped classroom concept to not only teach the students the theoretical basics but to enable them to independently formulate and integrate design problems, which can be abstracted as configuration problems, so that they develop a sustainable competence through learning-by-doing. The configuration problem of the student case study represented here is the positioning of a cast part for manufacturing, where the positioning is done via three subassemblies consisting of parts from a fixture toolbox. For this purpose, a development environment written in the Python programming language was set up, which uses an external Excel database as a knowledge base to provide the sizes of the fixture elements. Through a graphical user interface, the designer can specify how the fixture should be used so that the constraint solver can find a solution. If there are several possible solutions, an optimization loop is executed so that the designer can be given a clear recommendation. An interface to the CAD program Autodesk Inventor offers the possibility to build the fixture assembly of the selected solution from parameterized CAD models of the components by linking their custom coordinate systems. To reduce computing time, a case base is also provided for configurations that have already been created, so that existing subassemblies can be used if the same or similar configuration problem arises