Model-based system design of annealing simulators

We discuss several aspects of mechatronic product development processes, such as finding and evaluating design concepts and dependencies between design parameters. One of the key issues in the development of modern mechatronic systems is the benefit of consistent integration of mechanical, electrical, and electronic control and software aspects from the very beginning of the earliest design phases. Even for a single design problem defined by a given specification, different designers will probably respond with a variety of different design concepts, each of which may be acceptable in terms of meeting the specification. In the conceptual design phase, we propose that some aspects of design, such as hierarchy of parameters and modularity of the design, are analysed with conceptual models. The application presented in this paper shows the conceptual design of an experimental laboratory annealing simulator (anneal.sim-lab). Physical simulation of the annealing process requires consideration of different heating methods for various types of specimen. One critical step is the modularisation of sections (annealing, cooling, and quenching), and their geometric arrangement. We use a design structure matrix to analyse the requirements and their structure and demonstrate a realisation in a parametric 3D-CAD model.     

Development of an automated steering vehicle based on roadwaymagnets-a case study of mechatronic system design

Automated steering control is a crucial element of vehicle automation. The California PATH Program at the University of California at Berkeley has developed one such system using magnetic markers embedded under the roadway for lateral guidance. This system was demonstrated during the August 1997 National Automated Highway System Consortium Feasibility Demonstration, San Diego, CA, without a single failure. Developing a successful demonstration system not only required theoretical understanding of the various control problems involved, but also strong appreciation of all practical issues. In the paper, the comprehensive process of developing such automated steering control system is described. This process consists of control objectives' determination, system structure definition, vehicle dynamics validation, lateral sensing system development, steering actuator design, test track installation, control algorithm development, software/hardware integration, and vehicle testing. The entire process also serves as a good case study for mechatronic system design integrating mechanical components, electronic devices, intelligence, and feedback control to perform vehicle automation functions     

Modeling and design methodology for mechatronic systems

The integration of mechanical systems and microelectronics opens many new possibilities for process design and automatic functions. After discussing the mutual interrelations between the design of the mechanical system and digital electronic system the different ways of integration within mechatronic systems and the resulting properties are described. The information processing can be organized in multi levels, ranging from low level control through supervision to general process management. In connection with knowledge bases and inference mechanisms, intelligent control systems result. The design of control systems for mechanical systems is described, from modeling, identification to adaptive control for nonlinear systems. This is followed by solving supervision tasks with fault diagnosis. Then design tools for mechatronic systems are considered and examples of applications are given, like adaptive control of electromagnetic and pneumatic actuators, adaptive semiactive shock absorbers for vehicle suspension, and electronic drive-chain damping.     

Mechatronic design approach for engine management systems

Internal combustion engines with electronic management systems have developed to mechatronic systems. They basically consist of a thermodynamic process, electromechanic, hydraulic or pneumatic actuators, electronic sensors and one ore more digital control units with their specific software. In order to meet rising demands concerning drivability, emissions and consumption under the restriction of shorter development cycles, there is a rising need for modern identification methods (neural networks) and software/hardware tools (Rapid Control Prototyping (RCP), Hardware-in-the-Loop-Simulation) for the design of engine control units. In this contribution, a software/hardware environment for a mechatronic design approach for engine control systems is discussed. A dynamic engine test stand equipped with a RCP system is described which allows fast and comfortable design and testing of new control functions. Enlarged with an on-line indication system, a cylinder pressure based engine management system can be established, where the desired control settings are calculated by an upper level engine optimization. Time-variant optimization strategies for an improved exhaust-, consumption- and drivability performance were developed by means of adequate models of the engine behavior with fast neural networks.     

Model-integrated mechatronics - toward a new paradigm in the development of manufacturing systems

The traditional approach for the development of manufacturing systems considers the constituent parts of the system, i.e., mechanical, electronic, and software, to be developed independently and then integrated to form the final system. This approach is being criticized as inappropriate for the complexity and the dynamics of today's systems. This paper proposes an architecture that promotes model integration not only for implementation space artifacts but also in artifacts of the early analysis and design phases of the development process. The proposed architecture, which promotes reuse and significantly decreases development and validation time, is at the heart of a new paradigm called model-integrated mechatronics (MIM). MIM applies domain-specific modeling languages for the concurrent engineering of mechanical, electronic and software components of mechatronic systems. It simplifies the integrated development process of manufacturing systems by using as basic construct the mechatronic component. The MIM paradigm was utilized to define "Archimedes," a system platform that supports the engineer through a methodology, a framework, and a set of tools to automate the development process of agile mechatronic manufacturing systems.     

Design for control-a concurrent engineering approach formechatronic systems design

The well-accepted basis for developing a mechatronic system is a synergetic concurrent design process that integrates different engineering disciplines. In this paper, a general model is derived to mathematically describe the concurrent design of a mechatronic system. Based on this model, a concurrent engineering approach, called design for control (DFC), is formally presented for mechatronic systems design. Compared to other mechatronic design methodologies, DFC emphasizes obtaining a simple dynamic model of the mechanical structure by a judicious structure design and a careful selection of mechanical parameters. Once the simple dynamic model is available, in spite of the complexity of the mechanical structure, the controller design can be facilitated and better control performance can be achieved. Four design scenarios in application of DFC are addressed. A case study is implemented to demonstrate the effectiveness of DFC through the design and control of a programmable four-bar linkage     

Model relations between conceptual and detail design

Conceptual design, as an essential step towards successful mechatronic product development, should be supported by good models for the design map, which in turn expresses the relationship between the design parameters and the functional requirements. If feasible, these models should be mathematical. In this paper the close correlation between a good concept and its models is postulated. A theory is presented how these models are related to models employed for detail design and how good concept models can be characterised. The practical realisation of this characterisation relies on the decomposability of the whole design map in several low dimensional decoupled parts. This corresponds to Suh’s independence axiom. Modelling aspects of the development of an energy saving hydraulic variable valve train for combustion engines are used as a demonstrative example.     

Interface model enabling decomposition method for architecture definition of mechatronic systems

Solving a complex problem often requires a way to break it down into smaller, interconnected and manageable sub-problems, and then to join them together. The concept of breaking down a problem into smaller pieces is generally referred to as decomposition. The design of mechatronic systems is an example of such complex problems, as it is based on the integration of several disciplines, such as mechanical, electrical and software engineering. Decomposition is thus a common technique to help designers to obtain solutions for the design of mechatronic systems during the systems engineering process. However, an effective decomposition method which can fully solve the design problems of mechatronic systems has not yet been proposed in systems engineering.The goal of the paper is to formalise this decomposition method based on an interface model. This method is applicable to the architecture definition in the context of the design of mechatronic systems during their conceptual design phase. The proposed decomposition method provides designers with high-level guidance to help them to achieve the appropriate hierarchies and granularities for the architecture of mechatronic systems. The proposed decomposition method is applied and demonstrated using the systems engineering practices of a 3D measurement system.     

Safety analysis of mechatronic product lines

Most methodologies for the design and analysis of mechatronic systems target a single product. From a business perspective, successful product development requires shortening development times, reducing engineering costs and offering a greater variety of product options for customers. In software engineering, the software product line (SPL) technology has been developed to meet these conflicting goals, and several major companies have reported success stories resulting from SPL adoption. In mechanical engineering, similar methodologies have been developed under the name of product platforms. Methodologies for analyzing product qualities such as safety or reliability have been introduced for both SPL and product platforms. The problem with these methodologies is that they consider either software or mechanical product design, so they do not guide developers to find the best balance between the controller and the equipment to be controlled. Several system properties of a mechatronic product line should be investigated with mechatronic analysis methodologies before the development process branches to software, electronic and mechanical design. In particular, safety is one system property that can only be analyzed by considering both the equipment and its controller, so mechatronic methodologies early in the design are advantageous for discovering safety-related design constraints before costly design commitments are made. This paper extends the Functional Failure Identification and Propagation (FFIP) framework to the safety analysis of a mechatronic product line with options in software signal connections and equipment. The result of applying FFIP is that unsafe combinations of options are removed from the product line.