A Comprehensive Robust Design Approach for Decision Trade-Offs in Complex Systems Design

1999 ◽  
Vol 123 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Monu Kalsi ◽  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Systems Design ◽  
Decision Makers ◽  
Engineering Systems ◽  
Trade Offs ◽  
Design Variables ◽  
Complex Engineering ◽  
The Cost ◽  
Passenger Aircraft

In this paper we introduce a technique to reduce the effects of uncertainty and incorporate flexibility in the design of complex engineering systems involving multiple decision-makers. We focus on the uncertainty that is created when a disciplinary designer or design team must try to predict or model the behavior of other disciplinary subsystems. The design of a complex system is performed by many different designers and design teams, each of which may only have control over a portion of the total set of system design variables. Modeling the interaction among these decision-makers and reducing the effect caused by lack of global control by any one designer is the focus of this paper. We use concepts from robust design to reduce the effects of decisions made during the design of one subsystem on the performance of the rest of the system. Thus, in a situation where the cost of uncertainty is high, these tools can be used to increase the robustness, or independence, of the subsystems, enabling designers to make more effective decisions. To demonstrate the usefulness of this approach, we consider a case study involving the design of a passenger aircraft.

A Comprehensive Robust Design Approach for Decision Trade-Offs in Complex Systems Design

1999 ◽  
Author(s):  
Monu Kalsi ◽  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Systems Design ◽  
Decision Makers ◽  
Control Factor ◽  
Type I ◽  
Trade Offs ◽  
Design Variables ◽  
Complex Engineering ◽  
The Cost ◽  
Passenger Aircraft

Abstract In this paper we introduce a technique to reduce the effects of uncertainty and incorporate flexibility in the design of complex engineering systems involving multiple decision-makers. We focus on the uncertainty that is created when a disciplinary designer or design team must try to predict or model the behavior of other disciplinary subsystems. The design of a complex system is performed by many different designers and design teams, each of which may only have control over a portion of the total set of system design variables. Modeling the interaction among these decision-makers and reducing the effect caused by lack of global control by any one designer is the focus of this paper. We use concepts from robust design to reduce the effects of decisions made during the design of one subsystem on the performance of the rest of the system. Thus, in a situation where the cost of uncertainty is high, these tools can be used to increase the robustness, or independence, of the subsystems, enabling designers to make more effective decisions. This approach includes uncertainty caused by control factor variation (Type II robust design) and uncertainty caused by unknown nonlocal design information (Type I robust design). To demonstrate the usefulness of this approach, we consider a case study involving the design of a passenger aircraft.

Using Robust Design Techniques to Model the Effects of Multiple Decision Makers in a Design Process

1998 ◽  
Author(s):  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Interaction Analysis ◽  
System Modeling ◽  
Decision Makers ◽  
Engineering System ◽  
Entire System ◽  
Multiple Decision Makers ◽  
Complex Engineering ◽  
Passenger Aircraft ◽  
Complex Engineering System

Abstract In this paper we introduce a methodology to reduce the effects of uncertainty in the design of a complex engineering system involving multiple decision makers. We focus on the uncertainty that is created when a disciplinary designer or design team must try and predict or model the behavior of other disciplinary subsystems. The design of a complex system is performed by many different designers and teams, each of which only have control over a small portion of the entire system. Modeling the interaction among these decision makers and reducing the uncertainty caused by the lack of global control is the focus of this paper. We use well developed concepts from the field of game theory to describe the interactions taking place, and concepts from robust design to reduce the effects of one decision-maker on another. Response Surface Methodology (RSM) is also used to reduce the complexity of the interaction analysis while preserving behavior of the systems. The design of a passenger aircraft is used to illustrate the approach, and some encouraging results are discussed.

A Distributed Pool Architecture for Highly Constrained Optimization Problems in Complex Systems Design

2013 ◽  
Vol 13 (3) ◽  
Author(s):  
Vijitashwa Pandey ◽  
Zissimos P. Mourelatos
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Mechanical Design ◽  
Solution Process ◽  
Systems Design ◽  
Mixed Integer ◽  
Engineering Systems ◽  
Design Problems ◽  
Design Variables ◽  
Complex Engineering

Optimal design of complex engineering systems is challenging because numerous design variables and constraints are present. Dynamic changes in design requirements and lack of complete knowledge of subsystem requirements add to the complexity. We propose an enhanced distributed pool architecture to aid distributed solving of design optimization problems. The approach not only saves solution time but is also resilient against failures of some processors. It is best suited to handle highly constrained design problems, with dynamically changing constraints, where finding even a feasible solution (FS) is challenging. In our work, this task is distributed among many processors. Constraints can be easily added or removed without having to restart the solution process. We demonstrate the efficacy of our method in terms of computational savings and resistance to partial failures of some processors, using two mixed integer nonlinear programming (MINLP)-class mechanical design optimization problems.

Design of Complex Engineering Systems Using Multiagent Coordination

2016 ◽  
Author(s):  
Nicolás F. Soria ◽  
Mitchell K. Colby ◽  
Irem Y. Tumer ◽  
Christopher Hoyle ◽  
Kagan Tumer
Keyword(s):  
Autonomous Agents ◽  
Engineering Systems ◽  
Coordination Problem ◽  
Design Decisions ◽  
Multiagent Coordination ◽  
Trade Offs ◽  
Potential System ◽  
Complex Engineering ◽  
System States ◽  
Complex Engineering Systems

In complex engineering systems, complexity may arise by design, or as a by-product of the system’s operation. In either case, the root cause of complexity is the same: the unpredictable manner in which interactions among components modify system behavior. Traditionally, two different approaches are used to handle such complexity: (i) a centralized design approach where the impacts of all potential system states and behaviors resulting from design decisions must be accurately modeled; and (ii) an approach based on externally legislating design decisions, which avoid such difficulties, but at the cost of expensive external mechanisms to determine trade-offs among competing design decisions. Our approach is a hybrid of the two approaches, providing a method in which decisions can be reconciled without the need for either detailed interaction models or external mechanisms. A key insight of this approach is that complex system design, undertaken with respect to a variety of design objectives, is fundamentally similar to the multiagent coordination problem, where component decisions and their interactions lead to global behavior. The design of a race car is used as the case study. The results of this paper demonstrate that a team of autonomous agents using a cooperative coevolutionary algorithm can effectively design a Formula racing vehicle.

A Model-Based Formulation of Robust Design

2005 ◽  
Vol 127 (3) ◽  
pp. 388-396 ◽  
Author(s):  
Khalid Al-Widyan ◽  
Jorge Angeles
Keyword(s):  
Covariance Matrix ◽  
Robust Design ◽  
Design Problem ◽  
Engineering Systems ◽  
Design Environment ◽  
Design Task ◽  
Model Based ◽  
Functional Relations ◽  
Design Variables ◽  
Environment Parameters

Laid down in this paper are the foundations on which the design of engineering systems, in the presence of an uncontrollable changing environment, can be based. The changes in environment conditions are accounted for by means of robustness. To this end, a theoretical framework as well as a general methodology for model-based robust design are proposed. Within this framework, all quantities involved in a design task are classified into three sets: the design variables (DV), grouped in vector x, which are to be assigned values as an outcome of the design task; the design-environment parameters (DEP), grouped in vector p, over which the designer has no control; and the performance functions (PF), grouped in vector f, representing the functional relations among performance, DV, and DEP. A distinction is made between global robust design and local robust design, this paper focusing on the latter. The robust design problem is formulated as the minimization of a norm of the covariance matrix of the variations in PF upon variations in the DEP, aka noise in the literature on robust design. Moreover, one pertinent concept is introduced: design isotropy. We show that isotropic designs lead to robustness, even in the absence of knowledge of the statistical properties of the variations of the DEP. To demonstrate our approach, a few examples are included.

scholarly journals Low-cost monitoring buoys network tracking biogeochemical changes in lakes and marine environments – a regional case study

2018 ◽  
Vol 90 (10) ◽  
pp. 1631-1646 ◽  
Author(s):  
Alejandro J. Vitale ◽  
Gerardo M.E. Perillo ◽  
Sibila A. Genchi ◽  
Andrés H. Arias ◽  
María Cintia Piccolo
Keyword(s):  
High Frequency ◽  
Low Cost ◽  
Decision Makers ◽  
Shallow Waters ◽  
Global Level ◽  
Temperate Region ◽  
Coastal Marine ◽  
The Cost

AbstractLakes, rivers, estuaries and ocean waters control many important natural functions at the regional-global level. Hence, integrative and frequent long-term water monitoring is required globally. This paper describes the main features and innovations of a low-cost monitoring buoys network (MBN) deployed in a temperate region of Argentina. The MBN was designed to record extended time series at high-frequency, which is of great value for the scientific community, as well as for decision-makers. In addition, two innovative designs belonging to two versions of moored buoys (i.e. shallow waters and coastal marine waters) were presented. It was shown that the cost of either of two versions of the buoy is low, which can be considered as the main advantage.

Robust Design Through the Use of a Hybrid Genetic Algorithm

2002 ◽  
Author(s):  
Kurt Hacker ◽  
Kemper Lewis
Keyword(s):  
Robust Design ◽  
Hybrid Genetic Algorithm ◽  
Design Parameters ◽  
Optimization Approach ◽  
Engineering Systems ◽  
Local Optima ◽  
Good Design ◽  
Mean And Variance ◽  
The Mean

In this paper we present a hybrid optimization approach to perform robust design. The motivation for this work is the fact that many realistic engineering systems are mutimodal in nature with multiple local optima, and moreover may have one or more uncertain design parameters. The approach that is presented utilizes both local and global optimization algorithms to find good design points more efficiently than either could alone. The mean and variance of the objective function at a design point is calculated using Monte Carlo simulation and is used to drive the optimization process. To demonstrate the usefulness of this approach a case study is considered involving the design of a beam with dimensional uncertainty.

Application of cloud computing in financial services: an agent-oriented modelling approach

2018 ◽  
Vol 13 (4) ◽  
pp. 994-1006
Author(s):  
Subhas C. Misra ◽  
Kriti Doneria
Keyword(s):  
Cloud Computing ◽  
Financial Services ◽  
Decision Makers ◽  
Content Type ◽  
The Public ◽  
Similar Work ◽  
Doing Business ◽  
Trade Offs ◽  
Modelling Approach

Purpose Cloud computing is rapidly becoming the new norm of doing business. Lately, the extent of virtualization has enabled full-fledged cloud solution to become affordable, quantitatively and/or qualitatively. The purpose of this study is to explore the former in detail. In this paper, implementation of cloud-based services in the financial services, intermediaries and banking industry where security has always been the greatest concern are studied through actor-based stakeholder modelling. Drivers for adoption, benefits and trade-offs and challenges have been discussed in detail through a hypothetical comprehensive case study of a bank. Design/methodology/approach An actor-dependency-based technique for analyzing and modelling requirements prior to changes and charting out roadmap and rationale behind it all has been used. Through the use of i* modelling, dependencies and relationships between various stakeholders have been studied. Further, how decision makers in the financial services industry evaluate, consolidate and finally migrate to a new architecture is also explored. Findings Two hypothetical use cases on a hypothetical bank referred to as “The Bank” illustrate the technique and possible roadmap for implementation. Originality/value To the best of knowledge in the public domain, no similar work has been carried out with the perspective of modelling stakeholders and change management configuration in the financial services using cloud. This approach is valuable for augmenting technological advancements with business insights and spotting value in synergies of the sectors whenever and wherever apparent.

Including decision-makers preferences in the cost-deprivation trade-off during disaster interventions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Florian Diehlmann ◽  
Patrick Siegfried Hiemsch ◽  
Marcus Wiens ◽  
Markus Lüttenberg ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Humanitarian Logistics ◽  
Decision Makers ◽  
Weighted Sum ◽  
Trade Off ◽  
Content Type ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
The Cost

Purpose In this contribution, the purpose of this study is to extend the established social cost concept of humanitarian logistics into a preference-based bi-objective approach. The novel concept offers an efficient, robust and transparent way to consider the decision-maker’s preference. In principle, the proposed method applies to any multi-objective decision and is especially suitable for decisions with conflicting objectives and asymmetric impact. Design/methodology/approach The authors bypass the shortcomings of the traditional approach by introducing a normalized weighted sum approach. Within this approach, logistics and deprivation costs are normalized with the help of Nadir and Utopia points. The weighting factor represents the preference of a decision-maker toward emphasizing the reduction of one cost component. The authors apply the approach to a case study for hypothetical water contamination in the city of Berlin, in which authorities select distribution center (DiC) locations to supply water to beneficiaries. Findings The results of the case study highlight that the decisions generated by the approach are more consistent with the decision-makers preferences while enabling higher efficiency gains. Furthermore, it is possible to identify robust solutions, i.e. DiCs opened in each scenario. These locations can be the focal point of interest during disaster preparedness. Moreover, the introduced approach increases the transparency of the decision by highlighting the cost-deprivation trade-off, together with the Pareto-front. Practical implications For practical users, such as disaster control and civil protection authorities, this approach provides a transparent focus on the trade-off of their decision objectives. The case study highlights that it proves to be a powerful concept for multi-objective decisions in the domain of humanitarian logistics and for collaborative decision-making. Originality/value To the best of the knowledge, the present study is the first to include preferences in the cost-deprivation trade-off. Moreover, it highlights the promising option to use a weighted-sum approach to understand the decisions affected by this trade-off better and thereby, increase the transparency and quality of decision-making in disasters.

scholarly journals Spanning the complexity chasm: A research approach to move from simple to complex engineering systems

2014 ◽  
Vol 28 (4) ◽  
pp. 369-384 ◽  
Author(s):  
Vimal Viswanathan ◽  
Julie Linsey
Keyword(s):  
Design Thinking ◽  
Physical Models ◽  
Research Approach ◽  
Engineering System ◽  
Engineering Systems ◽  
Complex Engineering ◽  
Complex Engineering Systems ◽  
Complex System Design ◽  
Cost Effect

AbstractA multistudy approach is presented that allows design thinking of complex systems to be studied by triangulating causal controlled lab findings with coded data from more complex products. A case study illustration of this approach is provided. During the conceptual design of engineering systems, designers face many cognitive challenges, including design fixation, errors in their mental models, and the sunk cost effect. These factors need to be mitigated for the generation of effective ideas. Understanding the effects of these challenges in a realistic and complex engineering system is especially difficult due to a variety of factors influencing the results. Studying the design of such systems in a controlled environment is extremely challenging because of the scale and complexity of such systems and the time needed to design the systems. Considering these challenges, a mixed-method approach is presented for studying the design thinking of complex engineering systems. This approach includes a controlled experiment with a simple system and a qualitative cognitive-artifacts study on more complex engineering systems followed by the triangulation of results. The triangulated results provide more generalizable information for complex system design thinking. This method combines the advantages of quantitative and qualitative study methods, making them more powerful while studying complex engineering systems. The proposed method is illustrated further using an illustrative study on the cognitive effects of physical models during the design of engineering systems.

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