scholarly journals Sequential Updating of Quantitative Requirements for Increased Flexibility in Robust Systems Design

2019 ◽  
Vol 1 (1) ◽  
pp. 3531-3540
Author(s):  
Matthias Funk ◽  
Marcus Jautze ◽  
Manfred Strohe ◽  
Markus Zimmermann
Keyword(s):  
Information Exchange ◽  
Systems Design ◽  
Distributed Teams ◽  
Limited Information ◽  
Design Variables ◽  
Decision Variables ◽  
Subsystem Design ◽  
Sequential Updating ◽  
Early Decision ◽  
Independent Design

AbstractIn early development stages of complex systems, interacting subsystems (including components) are often designed simultaneously by distributed teams with limited information exchange. Distributed development becomes possible by assigning teams independent design goals expressed as quantitative requirements equipped with tolerances to provide flexibility for design: so-called solution-spaces are high-dimensional sets of permissible subsystem properties on which requirements on the system performance are satisfied. Edges of box-shaped solution spaces are permissible intervals serving as decoupled (mutually independent) requirements for subsystem design variables. Unfortunately, decoupling often leads to prohibitively small intervals. In so-called solution-compensation spaces, permissible intervals for early-decision variables are increased by a compensation mechanism using late-decision variables. This paper presents a multi-step development process where groups of design variables successively change role from early-decision to late-decision type in order to maximize flexibility. Applying this to a vehicle chassis design problem demonstrates the effectiveness of the approach.

Value-Driven Modeling of Tactical and Operational Decisions in Support of Aerospace Product-Service Systems Design

2015 ◽  
Author(s):  
Cassio D. Goncalves ◽  
Michael Kokkolaras
Keyword(s):  
Quality Function Deployment ◽  
Systems Design ◽  
Service Systems ◽  
Business Strategies ◽  
Functional Requirements ◽  
Operational Decisions ◽  
Design Engineers ◽  
Design Variables ◽  
Product Service ◽  
Product Service Systems

Competitive markets and complex business-to-business environments compel manufacturers to provide innovative service offerings along with their products. This necessitates effective methodologires for developing and implementing sucessful new business strategies. This article presents an approach to model tactical and operational decisions to support the design and development of Product-Service Systems (PSSs). A combination of Quality Function Deployment and Design-to-Cost techniques is proposed as the first step of a PSS design framework that aids design engineers to determine the relations among value to customer, functional requirements, design variables and cost. The objective is to identify PSS design alternatives that deliver value to customer while respecting cost targets. An aerospace software case study is conducted to demonstrate the proposed approach.

Engineering of a Virtual Community Platform

2004 ◽  
pp. 1-27
Author(s):  
Kerstin Rose ◽  
Leon Urbas ◽  
Alexander Kunzer ◽  
Martin Christof Kindsmuller ◽  
Sandro Leuchter
Keyword(s):  
Interaction Design ◽  
Information Exchange ◽  
Virtual Community ◽  
Distributed Teams ◽  
Online Journal ◽  
Human Machine Interaction ◽  
Internet Portal ◽  
Shared Workspaces ◽  
Machine Systems ◽  
Machine Interaction

UseWorld.net is a federated user adaptive Internet portal that supports information exchange and cooperation in research and development in the area of human machine interaction. It has been jointly developed with members of Center of Human-Machine-Systems (ZMMS, TU Berlin), Chair of Industrial Engineering and Ergonomics (RWTH Aachen), Chair for Industrial Design (University of Essen) and Center for Human-Machine-Interaction (ZMMI, University of Kaiserslautern). The portal is operated by an independent open incorporated society. It integrates manifold information services (online journal, different thematic link collections, conference database, expert database) and a sophisticated cooperation component to support distributed teams by providing shared workspaces. Software agents for community awareness tasks and a clean and consistent interaction design complete the solution and support the portal’s innovative operation concept, which intends to activate the users to become editors.

A Method for Distributed Optimization for Task Allocation

2009 ◽  
Author(s):  
Sheng Zhao ◽  
Baisravan HomChaudhuri ◽  
Manish Kumar
Keyword(s):  
Information Exchange ◽  
Optimization Problem ◽  
Global Solutions ◽  
Challenging Problem ◽  
Complex Environment ◽  
Dynamic Nature ◽  
Decision Variables ◽  
Wildland Firefighting

Allocation of a large number of resources to tasks in a complex environment is often a very challenging problem. This is primarily due to the fact that a large number of resources to be allocated results into an optimization problem that involves a large number of decision variables. Most of the optimization algorithms suffer from this issue of non-scalability. Further, the uncertainties and dynamic nature of environment make the optimization problem quite challenging. One of the techniques to overcome the issue of scalability that have been considered recently is to carry out the optimization in a distributed or decentralized manner. Such techniques make use of local information to carry out global optimization. However, such techniques tend to get stuck in local minima. Further, the connectivity graph that governs the sharing of information plays a role in the performance of algorithms in terms of time taken to obtain the solution, and quality of the solution with respect to the global solution. In this paper, we propose a distributed greedy algorithm inspired by market based concepts to optimize a cost function. This paper studies the effectiveness of the proposed distributed algorithm in obtaining global solutions and the phase transition phenomenon with regard to the connectivity metrics of the graph that underlies the network of information exchange. A case study involving resource allocation in wildland firefighting is provided to demonstrate our algorithm.

Casting and Milling Restrictions in Topology Optimization via Projection-Based Algorithms

2012 ◽  
Author(s):  
James K. Guest ◽  
Mu Zhu
Keyword(s):  
Topology Optimization ◽  
Continuation Methods ◽  
Minimum Length ◽  
Manufacturing Constraints ◽  
Element Space ◽  
Structure Topology ◽  
Design Variables ◽  
Unstructured Meshing ◽  
Independent Design ◽  
Minimum Length Scale

Projection-based algorithms are arising as a powerful tool for continuum topology optimization. They use independent design variables that are projected onto element space to create structure topology. The projection functions are designed so that geometric properties, such as the minimum length scale of features, are naturally achieved. They therefore offer an efficient means for imposing geometry-related design specifications and/or manufacturing constraints. This paper presents recent advances in projection-based algorithms, including topology optimization under manufacturing constraints related to milling and casting processes. The new advancements leverage the logic of recently proposed algorithms for Heaviside projection, including eliminating continuation methods on projection parameters and potential for using multiple design variables to achieve active projection of each phase used in design. The primary advantages of such an approach are that manufacturing restrictions are achieved naturally, without need for additional constraints, and that sensitivity calculations are efficient and straightforward. The primary drawback of the approach is that the so-called neighborhood maps require storage for efficient processing when using unstructured meshing.

Planetree Patient-Centered Care and the Healing Arts

2001 ◽  
Vol 7 (1) ◽  
pp. 17-19 ◽  
Author(s):  
Susan B. Frampton
Keyword(s):  
San Francisco ◽  
Information Exchange ◽  
Medical Center ◽  
Academic Medical Center ◽  
Hospital Staff ◽  
Holistic Health ◽  
Limited Information ◽  
Patient Centered ◽  
Centered Care ◽  
Healing Arts

In 1985, one of the most far-reaching experiments in the realm of holistic health was launched. The first of five Planetree Model Hospitals opened at a large academic medical center in San Francisco. Everything in the unique medical-surgical unit was designed with the patient's perspective in mind. The unit was the culmination of many years of work by a group of visionaries inspired, fittingly, by a single patient. This patient had undergone a traumatic, though not unusual, hospital stay. Limited information exchange between patient and providers, limited visiting hours, imper sonal treatment by hospital staff, and harsh institutional surroundings had resulted in anything but a healing experience. Motivated by a vision of what a hospital could be, Planetree was founded with the mission to change the way health care was delivered, and to personalize, humanize, and demystify the patient experience.

scholarly journals Assessing follow-up care compliance in children hospitalized for traumatic brain injuries

2020 ◽  
Vol 3 ◽  
Author(s):  
Hannah Bozell ◽  
Ashley Vetor ◽  
Jodi Raymond ◽  
Alexandra Hochstetler ◽  
Teresa Bell
Keyword(s):  
Healthcare Utilization ◽  
Information Exchange ◽  
Brain Injuries ◽  
Injury Severity ◽  
Limited Information ◽  
Post Discharge ◽  
Follow Up Care ◽  
Ed Visits

Background and Hypothesis: There is limited information regarding healthcare utilization and outcomes in children hospitalized for traumatic brain injury (TBI). Nearly 50% of adults hospitalized for trauma do not attend follow-up appointments, although completion of post-discharge care is associated with improved outcomes and decreased likelihood of subsequent emergency department (ED) visits. The Regestrief Institute Indiana Network for Patient Care (INPC) is a regional health information exchange (HIE) with health record data. This includes inpatient, outpatient, and ED visits, as well as imaging and lab data. The objective of this study is to use HIE data to assess long-term healthcare utilization, complications, and sequelae of pediatric patients hospitalized for TBI to see if follow-up compliance can identify patients at risk for post-TBI complications, including unplanned care, as well as long-term secondary health conditions.    Methods: 387 patients treated at a pediatric level 1 trauma center in Indiana admitted for TBI were identified using trauma registry data. EHR data in the INPC on patients for two years post-discharged were analyzed. Associations between compliance with follow-up care instructions given at discharge/subsequent medical visits and longitudinal utilization/outcomes were examined using Fisher’s exact test.     Results: After reviewing patient records, we found that 60.7% of patients received all follow-up care and 8.5% of patients received partial follow-up care, leaving 25.1% of patients receiving no follow up care and 5.7% of patients lost to follow-up after discharge. 12% of patients went to the ER for an injury-related issue and 6.2% of patients were readmitted. 19.4% of individuals experienced complications from injury while 12.4% of individuals had suspected sequela. Factors influencing recovery included race, age, insurance, injury severity, ICU admission, and ventilator usage.    Implications and Importance: Using HIE data can identify factors of hospitalized children vulnerable to not achieving optimal recovery and determine what care is critical to improving long-term health and quality of life outcomes. 

Maximizing Flexibility for Complex Systems Design to Compensate Lack-of-Knowledge Uncertainty

2019 ◽  
Vol 5 (4) ◽  
Author(s):  
Marco Daub ◽  
Fabian Duddeck
Keyword(s):  
Complex Systems ◽  
Complete Solution ◽  
Solution Space ◽  
Systems Design ◽  
Rigid Wall ◽  
Total System ◽  
Independent Manner ◽  
Design Variables ◽  
Knowledge Uncertainty ◽  
Lack Of Knowledge

Abstract The consideration of uncertainty is especially important for the design of complex systems. Because of high complexity, the total system is normally divided into subsystems, which are treated in a hierarchical and ideally independent manner. In recent publications, e.g., (Zimmermann, M., and von Hoessle, J. E., 2013, “Computing Solution Spaces for Robust Design,” Int. J. Numer. Methods Eng., 94(3), pp. 290–307; Fender, J., Duddeck, F., and Zimmermann, M., 2017, “Direct Computation of Solution Spaces,” Struct. Multidiscip. Optim., 55(5), pp. 1787–1796), a decoupling strategy is realized via first the identification of the complete solution space (solutions not violating any design constraints) and second via derivation of a subset, a so-called box-shaped solution space, which allows for decoupling and therefore independent development of subsystems. By analyzing types of uncertainties occurring in early design stages, it becomes clear that especially lack-of-knowledge uncertainty dominates. Often, there is missing knowledge about overall manufacturing tolerances like limitations in production or subsystems are not even completely defined. Furthermore, flexibility is required to handle new requirements and shifting preferences concerning single subsystems arising later in the development. Hence, a set-based approach using intervals for design variables (i.e., interaction quantities between subsystems and the total system) is useful. Because in the published approaches, no uncertainty consideration was taken into account for the computation of these intervals, they can possibly have inappropriate size, i.e., being too narrow. The work presented here proposes to include these uncertainties related to design variables. This allows now to consider lack-of-knowledge uncertainty specific for early phase developments in the framework of complex systems design. An example taken from a standard crash load case (frontal impact against a rigid wall) illustrates the proposed methodology.

Reliability-Based Design Optimization on Qualitative Objective With Limited Information

2018 ◽  
Vol 140 (12) ◽  
Author(s):  
Khaldon T. Meselhy ◽  
G. Gary Wang
Keyword(s):  
Objective Function ◽  
Design Optimization ◽  
Probability Distributions ◽  
Random Variables ◽  
Limited Information ◽  
Reliability Based Design Optimization ◽  
Mathematical Formula ◽  
Reliability Based Design ◽  
Design Structure ◽  
Design Variables

Reliability-based design optimization (RBDO) algorithms typically assume a designer's prior knowledge of the objective function along with its explicit mathematical formula and the probability distributions of random design variables. These assumptions may not be valid in many industrial cases where there is limited information on variable variability and the objective function is subjective without mathematical formula. A new methodology is developed in this research to model and solve problems with qualitative objective functions and limited information about random variables. Causal graphs and design structure matrix are used to capture designer's qualitative knowledge of the effects of design variables on the objective. Maximum entropy theory and Monte Carlo simulation are used to model random variables' variability and derive reliability constraint functions. A new optimization problem based on a meta-objective function and transformed deterministic constraints is formulated, which leads close to the optimum of the original mathematical RBDO problem. The developed algorithm is tested and validated with the Golinski speed reducer design case. The results show that the algorithm finds a near-optimal reliable design with less initial information and less computation effort as compared to other RBDO algorithms that assume full knowledge of the problem.

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