A Mars Exploration Concept Systems Design with an Innovative Unmanned Autonomous Vehicle and "Carrier" Ground Rover Configuration. Part I: System Design

2018 ◽  
Author(s):  
Michel Lacerda ◽  
Dongjin Park ◽  
Srujal Patel ◽  
Daniel Schrage
Keyword(s):  
System Design ◽  
Autonomous Vehicle ◽  
Systems Design ◽  
Mars Exploration ◽  
Concept Systems

scholarly journals MANAGEMENT PRACTICES AND COST SYSTEM DESIGN: EVIDENCE FROM JORDANIAN MANUFACTURING COMPANIES

2020 ◽  
Vol 8 (1) ◽  
pp. 920-929
Author(s):  
Majdy I. Zuriekat
Keyword(s):  
System Design ◽  
Management Practices ◽  
Systems Design ◽  
Just In Time ◽  
Manufacturing Companies ◽  
Total Quality ◽  
Cost System ◽  
Study Results ◽  
Managerial Implications ◽  
Study Questionnaire

Purpose: The purpose of this study is to reveal and examine the nature of costing systems design alongside the usage of new manufacturing practices in Jordanian Manufacturing Companies. Design/Methodology/Approach: For carrying out the study, 86 managers from 43 manufacturing companies received the study questionnaire from which 56 were valid for data analysis. The study results are presented using multiple regression analysis. Findings: The results using multiple regressions indicate that Just in Time (JIT), Total Quality Management (TQM) and Product Diversity (PD) has a significant influence on costing systems design. Implications: This study provides evidence on the importance of using management practices as a driver for companies to use a broader perspective for designing costing systems. Responding managers have now empirical evidence regarding the manufacturing practices needed to design costing systems to their companies. Originality/Value: This is the first attempt to examine the manufacturing practices as a driver for cost system design. The study also provides significant managerial implications on how to use manufacturing practices to ensure better cost system design.

scholarly journals Biased Information Passing Between Subsystems Over Time in Complex System Design

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Jesse Austin-Breneman ◽  
Bo Yang Yu ◽  
Maria C. Yang
Keyword(s):  
Complex System ◽  
System Design ◽  
Large Scale ◽  
Early Stage ◽  
Systems Design ◽  
System Level ◽  
Worst Case ◽  
Early Stage Design ◽  
Complex System Design ◽  
Biased Information

During the early stage design of large-scale engineering systems, design teams are challenged to balance a complex set of considerations. The established structured approaches for optimizing complex system designs offer strategies for achieving optimal solutions, but in practice suboptimal system-level results are often reached due to factors such as satisficing, ill-defined problems, or other project constraints. Twelve subsystem and system-level practitioners at a large aerospace organization were interviewed to understand the ways in which they integrate subsystems in their own work. Responses showed subsystem team members often presented conservative, worst-case scenarios to other subsystems when negotiating a tradeoff as a way of hedging against their own future needs. This practice of biased information passing, referred to informally by the practitioners as adding “margins,” is modeled in this paper with a series of optimization simulations. Three “bias” conditions were tested: no bias, a constant bias, and a bias which decreases with time. Results from the simulations show that biased information passing negatively affects both the number of iterations needed and the Pareto optimality of system-level solutions. Results are also compared to the interview responses and highlight several themes with respect to complex system design practice.

Multiobjective Collaborative Optimization

1997 ◽  
Author(s):  
Ravindra V. Tappeta ◽  
John E. Renaud
Keyword(s):  
System Design ◽  
Systems Design ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Accurate Estimation ◽  
Successful Implementation ◽  
Design Environment ◽  
Comprehensive Overview ◽  
Design Problems ◽  
Multidisciplinary Systems

Abstract This investigation focuses on the development of modifications to the Collaborative Optimization (CO) approach to multidisciplinary systems design, that will provide solution capabilities for multiobjective problems. The primary goal of this research is to provide a comprehensive overview and development of mathematically rigorous optimization strategies for MultiObjective Collaborative Optimization (MOCO). Collaborative Optimization strategies provide design optimization capabilities to discipline designers within a multidisciplinary design environment. To date these CO strategies have primarily been applied to system design problems which have a single objective function. Recent investigations involving multidisciplinary design simulators have reported success in applying CO to multiobjective system design problems. In this research three MultiObjective Collaborative Optimization (MOCO) strategies are developed, reviewed and implemented in a comparative study. The goal of this effort is to provide an in depth comparison of different MOCO strategies available to system designers. Each of the three strategies makes use of parameter sensitivities within multilevel solution strategies. In implementation studies, each of the three MOCO strategies is effective in solving two multiobjective multidisciplinary systems design problems. Results indicate that these MOCO strategies require an accurate estimation of parameter sensitivities for successful implementation. In each of the three MOCO strategies these parameter sensitivities are obtained using post-optimality analysis techniques.

Supporting Proximate Communities with P3-Systems

2005 ◽  
pp. 215-250 ◽  
Author(s):  
Quentin Jones ◽  
Sukeshini A. Grandhi
Keyword(s):  
System Design ◽  
Systems Design ◽  
Community Member ◽  
Community Members ◽  
Online Interactions ◽  
Physical Location ◽  
Virtual Spaces ◽  
Physical Spaces ◽  
User Location

In this chapter we examine systems that link People-to-People-to-geographical-Places, which we label P3-Systems. Four major P3-Systems design approaches have been identified by an analysis of systems prototyped to date: (1) People Centric P3-System design that use absolute user location, based on awareness of where somebody is located (e.g., Active Badge); (2) People Centric P3-System design based on user co-location/proximity (e.g., Hocman); (3) Place Centric P3-System design based on the use of virtual spaces that contain representations of user’s use of physical spaces (e.g., ActiveMap); and (4) Place Centric P3-System design based on the use of virtual spaces that contain online interactions related to physical location (e.g., Geonotes). This chapter explores how proximate community member interactions can potentially be well supported by P3-Systems through the improved geographical contextualization and coordination of interactions and the identification of previously unidentified location based affinities between community members.

Multiobjective Collaborative Optimization

1997 ◽  
Vol 119 (3) ◽  
pp. 403-411 ◽  
Author(s):  
R. V. Tappeta ◽  
J. E. Renaud
Keyword(s):  
System Design ◽  
Systems Design ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Accurate Estimation ◽  
Successful Implementation ◽  
Design Environment ◽  
Comprehensive Overview ◽  
Design Problems ◽  
Multidisciplinary Systems

This investigation focuses on the development of modifications to the Collaborative Optimization (CO) approach to multidisciplinary systems design, that will provide solution capabilities for multiobjective problems. The primary goal of this paper is to provide a comprehensive overview and development of mathematically rigorous optimization strategies for Multiobjective Collaborative Optimization (MOCO). Collaborative Optimization strategies provide design optimization capabilities to discipline designers within a multidisciplinary design environment. To date these CO strategies have primarily been applied to system design problems which have a single objective function. Recent investigations involving multidisciplinary design simulators have reported success in applying CO to multiobjective system design problems. In this research three Multiobjective Collaborative Optimization (MOCO) strategies are developed, reviewed and implemented in a comparative study. The goal of this effort is to provide an in depth comparison of different MOCO strategies available to system designers. Each of the three strategies makes use of parameter sensitivities within multilevel solution strategies. In implementation studies, each of the three MOCO strategies is effective in solving a multiobjective multidisciplinary systems design problem. Results indicate that these MOCO strategies require an accurate estimation of parameter sensitivities for successful implementation. In each of the three MOCO strategies these parameter sensitivities are obtained using post-optimality analysis techniques.

scholarly journals FARUL3S: a New Framework for Agile Regulated Ultra-Large-Scale Software Systems

2021 ◽  
Author(s):  
Amira KSIKSI
Keyword(s):  
System Design ◽  
Smart City ◽  
Large Scale ◽  
Complex Adaptive System ◽  
Systems Design ◽  
Domain Model ◽  
Design Rule ◽  
Software Systems ◽  
Management And Development ◽  
Complex Adaptive

<div>The Ultra-Large-Scale Software (ULSS) systems development challenges today’s software management and development approaches. Northrop et al. (2006) revealed three broad areas of challenges [1]. To deal with those challenges, they propose an interdisciplinary portfolio of research. In particular, we address the design and evolution challenge by focusing on the design area of research. In order to regulate the ULSS systems, the traditional software engineering tools face challenges as they are top-down so they deal with each domain model separately. To address the domain diversity like in the smart city systems, we propose the Framework for Agile Regulated Ultra Large Scale Software System (FARUL3S) to look at the ULSS system from bottom-up. The FARUL3S is a user-centered solution that aims at combining the complex adaptive system, the financial economics as well as the engineering systems design. Our contribution aims to regulate and constrain the ULSS systems by using architectural agreements and other rules. In this paper, we provide a detailed description of the FARUL3S steps. Our Framework generates a system Design Rule Hierarchy (DRH) so it can be used to constrain the entire system design. In the future, we will provide an illustration of the FARUL3S adoption on the management and design of different smart city services to ensure the efficiency of our solution.</div>

Pseudo-Hierarchical Multistage Model for System of Systems Design and Operations

2007 ◽  
Author(s):  
Harrison M. Kim ◽  
I. Jessica Hidalgo
Keyword(s):  
Decision Making ◽  
Design Optimization ◽  
System Design ◽  
Systems Design ◽  
System Of Systems ◽  
Sequential Approach ◽  
Multistage Model ◽  
Stage System ◽  
System Design Optimization ◽  
Alternating Directions Method

This paper describes a multilevel, multistage approach to system of systems design optimization where a system design is linked with system allocation along the multistage decision making horizon. The approach is composed of two parts: pseudo-hierarchical formulation (i.e., how to model the stages of multiple, separate decision making processes), and multistage coordination (i.e., how efficiently the proposed model would perform). The pseudo-hierarchical formulation integrates multilevel optimization and multistage programming to capture level-by-level and stage-by-stage system design optimization. The multistage coordination is based on the alternating directions method that is incorporated as an efficient means to solve this inherently largescale optimization problem. An example on collaborative system operation and design between an airline and an aircraft manufacturer validates the methodology where an airline plans to introduce multiple new aircraft to capture dynamically changing demand of the customers. The proposed methodology is validated against the all-in-one approach and the sequential approach.

Sign in / Sign up

Export Citation Format

Share Document