Journal of Integrated Design and Process Science

Obsolescence is the fact that an entity (physical or logical) is becoming outdated or no longer possesses the required level of performance. The objectives of this article are twofold. First, it is intended to contribute to the understanding of obsolescence propagation. Secondly, two supporting approaches for the Identification and Assessment phases are proposed: the House of Obsolescence and the System Obsolescence Criticality Analysis. The former allows the mapping of obsolescence propagation via dependencies, whether imposed changes are desired or imposed, by external actors to the system architecture. Whereas, the objective of the latter is to assign an obsolescence criticality index to the identified risks in order to prioritize them for solution or mitigation determination during the analysis phase. The tools make extensive use of the modeled system knowledge through the application of Systems Engineering. The application of these approaches is presented through an illustrative study.

The rise in attacks on Industrial Control Systems (ICS) makes it imperative for the anomaly detection mechanisms (ADMs) to be complete with respect to a set of attacks. In this work, a method is proposed to create and launch simulated attacks on ICS. In the proposed method, referred to as ICS Resilience (ICSRes), attacks are generated using a tool suite named A6. A6 mutates data exchanged between any two PLCs connected via the communications network as well as between a PLC and the sensors and actuators connected to it via a Remote Input/Output (RIO) unit. It consists of both single-point and multi-point mutations that can be manipulated in static or in dynamic form. A two-part case study was conducted to assess the effectiveness and completeness of ICSRes and A6 when compared with that of launching humanly designed attacks. Effectiveness is defined as the ability to detect complex attacks that causes process anomalies and completeness refers to the ability to detect the type of attack. In Part I of the study, the attacks were automatically generated and launched using A6. In Part II a set of attacks was generated and launched manually while participating in an international cyber-exercise. In both parts of the study three ADMs, installed in an operational water treatment testbed, were used to assess their completeness with respect to the generated attacks. The results demonstrate the effectiveness of ICSRes and the tools in highlighting the strength and weaknesses of the ADMs and the value of using A6.

A mandatory requirement for the concept of intelligent systems and of digital or cyber-physical twins is the availability of high-quality data. Therefore, the authors investigate the possibility to integrate sensors, actuators and information technologies in standardized machine elements such as screws, bearings and couplings. In this paper, the focus is on sensing machine elements, which are a sub-category of mechatronic machine elements. To gain insights about those in development as well as to verify and validate their functionality, prototypes are needed. Those prototypes should help the designer to gain knowledge about the product in development and they should preferably be developed with low efforts. Therefore, a method is proposed to analyse concepts of mechatronic machine elements, especially sensing machine elements, regarding critical aspects that may interfere with the functionality of the product. The method is based on analysing the flow of the signal that is used for the measurement, starting from its mechanical origin and ending at the analysis unit. Different examples of sensing machine elements are given in this article and the respective flow of the usable signal is analysed, leading to the identification of subsystems that can be tested individually. Based on this, prototypes for the subsystems are developed and introduced.

One of the challenges in large volume metrology is that it is often difficult or impossible to control the ambient conditions in which the object is to be measured. Dimensional measurement results vary with those conditions and it becomes necessary to apply some form of compensation. Thermal compensation of dimensional measurement is primarily reliant on the ability to properly measure temperature across the volume, which can differ by several degrees, but conventionally a uniform scaling has been applied. This paper focuses upon temperature sensor network planning improvement to facilitate thermal compensation. Beyond assembly environments, data from sensor networks are increasingly used to make decisions, but appropriate design and testing of such networks can be limited. As the demand for production digital twins increase, appropriate methods to quantify and optimise uncertainty to improve confidence will be invaluable. A virtual test bed has been created for the design, test, and optimisation of temperature sensor networks supported by physical simulation. Sensor networks have been used to take virtual measurements from a known temperature distribution and used to reconstruct the temperature distribution. Random search optimisation on a subset of the sensor network was carried out to determine some initial rules for sensor network design. The positioning of the sensors within the measurement volume and the method of reconstructing the temperature field was found to be more important than the capability of the individual sensors. Two means of interpolating the ambient field have been investigated: polynomial fitting and kriging. Temperature sensor networks appeared more sensitive to changes at the spatial boundary and these positions seem to be most critical for accurate reconstruction. In the case of the barrel section assembly it was found that asymmetric sensor heights produced better results, for example. A polynomial interpolation model using a 16-sensor network with 0.1 °C (confidence interval, k = 2) uncertainty sensors could produce a consistent temperature reconstruction error of ~0.04 °C RMS, corresponding to a thermal expansion error of ~1.5 μm in aluminium over a 1.6 m-tall structure.

In engineering, design decisions in one domain exhibit multiple consequences in other domains. These consequences result from the often more or less hidden coupling between the different design domains. In order to examine these consequences, models need to be created. In practice, this is challenging due to the exchange of data between different engineering domains, since different software applications are often used and the effort involved with manual model creation. In this paper, we explore the use of graph-based design languages in a Model-Based Systems Engineering (MBSE) approach to link the digital factory with building design. We also show that the use of a common formal representation based on the Unified Modeling Language (UML) supports the interoperability between the two domains. Finally, we demonstrate how the engineering knowledge for the preliminary design of a factory building can be formally described using graph-based design languages and how the production line of the digital factory can then be used as an input to automatically create valid preliminary designs for the factory building. 1

Optimization metaheuristics have become necessary due to the growing demand for better and more realistic designs. This paper proposes a metaheuristic-based approach for solving design problems in a reasonable time while browsing large spaces of solutions. The objective of this article is to compare the performance of two methods Genetic Algorithm GA and Particle swarm optimization PSO, combined with A* algorithm, in solving a constrained facility layout problem. The two chosen metaheuristics have been successfully applied in many search problems. We consider their speed and performance. The performance of the obtained solutions is measured in terms of the total distance traveled by products in the workshop. In order to determine the shortest path in a realistic way between workstations in a given irregular area (with aisle structure, or material storage areas, lunchrooms and offices), the A* algorithm was integrated with them. The comparison therefore concerns <GA, A*> and <PSO, A*>. GA and PSO algorithms generate configurations for which the shortest path for any couple of machines is identified through the A* search algorithm taking into account of obstacles. The mathematical model used and the parameters of the genetic algorithm are those developed in (Besbes et al. 2019). The numerical results show the feasibility and effectiveness of both approaches. Our results demonstrate that GA yields a better solution than Particle Swarm Optimization in total distance travelled while PSO is faster.

Robotic assembly of mating parts (peg-in-hole (PiH)) inevitably encounters misalignments. Although passive end-effector compliance is key to successful alignment during the assembly, the literature does not propose many solutions for large misalignments, which is relevant to applications such as compliance of a robot end-effector for train fluid servicing. The results from physical experiments indicate insertion forces that are too large for practical applications, even with small misalignments. This preliminary study applies a hybrid approach combining physical experiments and simulation modelling for large motion PiH coupling with end-effector compliance. This provides a platform for investigating insertion force during misaligned coupling. The simulation model contains configurable parameters for robot compliance and PiH friction which are informed by the physical experiment results. The many robot compliances are lumped as two torsional springs on the pitch and yaw motion axis of the robot arm model. The simulation model is then calibrated using the physical results without having to conduct further intensive physical experiments. The calibrated model represents the physical measurements to a satisfactory degree, however its performance can still be improved.

This paper develops a novel implementation of energy-based homogenization method, which has rigorous mathematical foundation of the homogenization method, and also efficiently and accurately predict the mechanical performance of composite materials. The feature extraction, domain discretization and periodic boundary condition application are carried out automatically in this method. Besides, this model remains a fairly small scale and it could be directly embedded into structure optimization algorithms. The numerical calculation could be easily implemented with a commercial computer aided engineering (CAE) software and the integration algorithm was realized by the third-party language. This article explains the scheme of the CAE/CAD integration in homogenization method and the theoretical model of the energy-based homogenization for cellular solid element and shell element. Furthermore, two examples for cellular solid and stiffened plate, and its implementation in cellular material design are presented to illustrate the verification of the proposed method.