Lifecycle Design of Disruptive SCADA Systems for Waste-Water Treatment Installations

Capacity to remotely monitor and control systems for waste-water treatment and to provide real time and trustworthy data of system’s behavior to various stakeholders is of high relevance. SCADA systems are used to undertake this job. SCADA solutions are usually conceptualized and designed with a major focus on technological integrability and functionality. Very little contributions are brought to optimize these systems with respect to a mix of target functions, especially considering a lifecycle perspective. In this paper, we propose a structured methodology for optimizing SCADA systems from a lifecycle perspective for the specific case of waste-water treatment units. The methodology embeds techniques for handling entropy in the design process and to assist engineers in designing effective solutions in a space with multiple constrains and conflicts. Evolutionary multiple optimization algorithms are used to handle this challenge. After the foundation of the theoretical model calibrated for the specific case of waste-water treatment units, a practical example illustrates its applicability. It is shown how the model can lead to a disruptive solution, which integrates cloud computing, IoT, and data analytics in the SCADA system, with some competitive advantages in terms of flexibility, cost effectiveness, and increased value added for both integrators and beneficiaries.

Data Assimilation Mechanism for Lifecycle Simulation Focusing on Process Behaviors

Systematic lifecycle design and management are promising approaches for constructing sustainable product lifecycle systems. Lifecycle simulation (LCS) has been used to evaluate a product lifecycle in the design phase from both the environmental and economic perspectives. Based on material flows through each process of the product lifecycle, the LCS calculates the time variation in environmental loads, cost, and profit. In each process of the LCS model, functions that regulate the behaviors of the process, called behavior functions, are set, and these functions control material flows. Previously, we proposed a data-assimilated LCS method that combines data assimilation (DA) with LCS to realize adaptive management based on actual states of the product lifecycle. In this previous development, the DA mechanism modified the material flows of an entire lifecycle in the simulation model based on actual flows observed in each process at the time of the DA. However, because process behaviors were not modified, the gap between material flows predicted by the simulation and the flows of the actual lifecycle increased over time. To overcome this limitation, in this study, we propose a new DA mechanism that modifies the behaviors of un-observed processes based on observed material flows. The proposed DA mechanism uses the response surface methodology to estimate the behaviors while tracing the causal relation in the LCS model in reverse. A case study on a photovoltaic panel reuse business showed that the DA mechanism successfully merged the observed data into the process behaviors in the LCS model including the processes where no data were observed, thereby improving the accuracy of the simulation for future prediction. Systematically analyzing the current and future process states of the product lifecycle can support decision-making in lifecycle management.

A Literature Review of Design Decision Making in Disruptive Technological Innovations of New Products

This paper reviews the information available on specifics of the design decision-making process for the case of disruptive technological innovations associated with new products and systems. It defines the term “disruptive technological innovation,” provides with the explanation of decision-making methodology peculiarities for this type of innovation, and describes currently existing techniques and tools to support design decision making in case of disruptive technological innovations. The current paper relates to decision making in systems engineering and design, and therefore deals with the design decision making. The terms “disruptive technologies” and “disruptive innovations” appeared at the end of the 1990s. Researchers frequently mention disruptive innovations and technologies in the description of technical products for different industries: aircraft, automotive, food, petroleum, etc. A disruptive technological innovation is defined as a combination of disruptive technology and disruptive innovation. A new product can be relatively a simple device like an unmanned aerial vehicle and a smartphone, or a complex system like a modern aerospace vehicle or a space information network. Being an innovative developed product, it possesses peculiarities influencing the product development phase of the product lifecycle design decision-making process and accompanying supporting techniques and tools. This review investigates the specifics of design decision making of disruptive technologically innovative products that influence different stages of the product development phase in their product lifecycles. The paper combines aspects of systems engineering with innovation theory, key elements of the design of complex systems, and highlights the product development phase of the product lifecycle design decision-making process.

Efficient Fatigue and Ratcheting Computation in Case of Multi-Parameter Loading

Cyclic and over-elastic loading can lead to an accumulation of plastic strains. If there is a cyclic load, which is driven by a single parameter, the lifecycle design can be very costly in terms of computational effort. If more than one cyclic load parameter is to be taken into account, which is then a multi-parameter loading, this task can become even more complex and costly. To solve this problem efficiently, different techniques are proposed. One of these techniques is based on step-by-step calculations of the strain ranges for a reduced set of loadings. Once these strain ranges are known, the accumulated state for each individual load case can be estimated using the Simplified Theory of Plastic Zones (STPZ), which requires just a few linear elastic analyses. It is shown that cyclic loads, which occur in intervals, can be replaced by interval-free calculations, which reduce the computational effort enormously. All these techniques lead to a procedure, which delivers good estimations in terms of post-shakedown quantities with very low computational effort compared to incremental step-by-step calculations. The results of the STPZ are presented by an example. A thick-walled cylinder is loaded with a constant axial force and subjected to cyclic shear and cyclic internal pressure. In general, for structures exhibiting ratcheting, hundreds or more load cycles must be analysed via step-by-step calculations until the shakedown state is reached. Using the STPZ, post-shakedown quantities, including strain ranges and accumulated strains can be estimated efficiently and the structure can be designed according to the rules of the ASME Codes. The computational effort and the quality of the results of the STPZ are compared with a step-by-step calculation.

Multicriteria analysis and information modelling in management of built environment

Building Information Modelling (BIM) proves to be the most urgent trend in construction for the last years. Still the major part of this issue is dedicated only to the first stages of building lifecycle: design and construction. This article goal is to provide a critical overview on recent achievements in BIM application for the different steps of building lifecycle as well as ongoing digitalization of facility management. The paper explores the importance of applying mathematical modelling and multicriteria analysis such as Analytical Hierarchy Process (AHP) and fuzzy logic in management of built environment and provides recent examples of such applications consequently exploring its potential. Method of analysis in this article is horizontal analysis of publication activity in related research topic. Different levels of digital built environment are considered: from building (BIM) to the whole city (GIS). The result of the research reveal that emergence of scan-to-BIM technology brings benefits not only for the buildings which are designed with BIM models (current situation in the market) but for the buildings which are already built (as-built BIM).

Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities

The rapid rise in technologies for data collection has created an unmatched opportunity to advance the use of data-rich tools for lifecycle decision-making. However, the usefulness of these technologies is limited by the ability to translate lifecycle data into actionable insights for human decision-makers. This is especially true in the case of sustainable lifecycle design (SLD), as the assessment of environmental impacts, and the feasibility of making corresponding design changes, often relies on human expertise and intuition. Supporting human sensemaking in SLD requires the use of both data-driven and user-driven methods while exploring lifecycle data. A promising approach for combining the two is through the use of visual analytics (VA) tools. Such tools can leverage the ability of computer-based tools to gather, process, and summarize data along with the ability of human experts to guide analyses through domain knowledge or data-driven insight. In this paper, we review previous research that has created VA tools in SLD. We also highlight existing challenges and future opportunities for such tools in different lifecycle stages—design, manufacturing, distribution and supply chain, use-phase, end-of-life (EoL), as well as life cycle assessment (LCA). Our review shows that while the number of VA tools in SLD is relatively small, researchers are increasingly focusing on the subject matter. Our review also suggests that VA tools can address existing challenges in SLD and that significant future opportunities exist.