A System Level Approach to the Design of an Industrial Ecosystem

1997 ◽  
Author(s):  
Reid Bailey ◽  
Janet K. Allen ◽  
Bert Bras ◽  
Farrokh Mistree
Keyword(s):  
Industrial Ecology ◽  
Initial Step ◽  
Design Tool ◽  
System Level ◽  
Design Problems ◽  
Industrial Ecosystem ◽  
Engine Design ◽  
Concept Exploration ◽  
Industrial Ecosystems ◽  
Negative Environmental Impact

Abstract Industrial ecology is a nascent concept in which systems of industries work together to reduce their net negative environmental impact. The work in this paper represents an initial step towards the advancement of industrial ecology through quantitative analysis. A system dynamics model of an existing industrial ecosystem is developed in STELLA® and used to represent the system level behavior. A design tool, the Robust Concept Exploration Method (RCEM), that has been used previously for more traditional design problems, e.g., engine design and airplane design, is successfully applied to the system level design of an industrial ecosystem. The results in this paper are intended to provide support for decision makers in complex industrial ecosystems and, more importantly, to increase the knowledge about designing industrial ecosystems. As the concept of industrial ecology progresses, the analysis of ecosystems will become more complex, increasing the need for design at the system level to be addressed with tools such as the RCEM.

scholarly journals Synergistic Evaluation and Constraint Factor Analysis on Urban Industrial Ecosystems of Traditional Industrial Area in China

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Chengpeng Lu ◽  
Wei Ji ◽  
Zhiliang Liu ◽  
Shuheng Dong ◽  
Bing Xue
Keyword(s):  
Industrial Ecology ◽  
Industrial Area ◽  
Northeastern China ◽  
Liaoning Province ◽  
System Level ◽  
Ecological Environment ◽  
Ecosystem Development ◽  
Constraint Factors ◽  
Industrial Ecosystem ◽  
Major Constraint

Industrial ecology is an advanced form and ideal model of modern industrial development, in which the industrial ecosystem is the core. Based on the PSR model, this paper builds a comprehensive evaluation index system for urban industrial ecosystem development and selects 14 prefecture-level cities in Liaoning Province of the traditional industrial area in Northeastern China as cases to calculate the development level of its industrial ecosystem during 2000–2018 using an improved Topsis method and then to conduct a spatial visualization analysis. Finally, based on the “stress-state-response” subsystem, this paper diagnoses the constraints for industrial ecosystem development, which can provide a reference basis for decision-making in industrial ecology of traditional industrial area represented by those in Northeast China. The results show the following: (1) From 2000 to 2018, the industrial ecology of the 14 cities in Liaoning Province was at a medium level. Except for Shenyang and Dalian with the rapid development, the difference of industrial ecosystem development for other cities was relatively small. (2) From 2000 to 2018, the industrial ecosystem development of each city was in a status of “either increasing, or decreasing, or fluctuating,” which generally raised first and then decreased. Regarding spatial difference, the development exhibited a “center-periphery” pattern, with Shenyang and Dalian as the “dual-core” that were increasingly strengthened with significantly high-level industrial ecology. (3) At system level, PSR constraint grades for the industrial ecosystem development in the 14 cities of Liaoning Province were different. Constraint grades in the pressure subsystem, the state subsystem, and the response subsystem for the industrial ecosystem of Liaoning were 45.73%, 20.01%, and 34.34%, respectively, indicating that the lack of human response to the ecological environment and the pressure of human activities on the ecological environment during the industrial economy development were the main constraints affecting the process of industrial ecology in these cities. (4) Due to the differences in geographical environments, economic bases, industrial structures, and local development contexts, the major constraint factors of industrial ecosystem development in different cities are significantly different and complicated; however, there are five factors that are generally considered as major constraint factors in all cities, i.e., regional GDP, number of labor force employed in the secondary industrial sector, gross investment in fixed assets, amount of industrial sulfur dioxide removal, and production value from “three-wastes” comprehensive utilization. At last, this paper puts forward some recommendations and suggestions for providing scientific support for industrial ecosystem construction in the traditional industrial area of Northeastern China.

Strategic Management of Industrial Ecosystems Based on the Platform Concept

2021 ◽  
Vol 27 (10) ◽  
pp. 751-765
Author(s):  
V. V. Glukhov ◽  
A. V. Babkin ◽  
E. V. Shkarupeta ◽  
V. A. Plotnikov
Keyword(s):  
Strategic Management ◽  
Ecosystem Management ◽  
Structural Model ◽  
Industrial Ecology ◽  
Data Interpretation ◽  
Agglomerative Clustering ◽  
Economic Sectors ◽  
Ecosystem Research ◽  
Industrial Ecosystem ◽  
Industrial Ecosystems

Aim. The presented study aims to develop a structural model for industrial ecosystem management and to propose strategies for the industrial ecosystem orchestrator.Tasks. The authors systematize the landscape of existing research in the field of ecosystems; identify the problem and determine the research gap; develop the concept of ecosystem entity; determine the specific features of industrial ecosystem management; develop a structural model for industrial ecosystem management based on the platform concept; recommend strategies for the industrial ecosystem orchestrator.Methods. This study uses general scientific methods (synthesis, generalization, content analysis, graphical data interpretation), economic and statistical methods (correlation and regression analysis, mathematical statistics, expert methods, principal components analysis, hierarchical agglomerative clustering). As part of a study of economic sectors and digital technologies, the market structure is analyzed, and the dynamics of development indicators of digitalization processes is described.Results. The landscape of modern ecosystem research, types and properties of ecosystems, the composition of actors and exchange resources by ecosystem type are systematized, the concept of ecosystem entity is developed, and the specific features of industrial ecosystem management are determined. A structural model for industrial ecosystem management is developed. Four strategies for the industrial ecosystem orchestrator are recommended: increasing value, building trust, activating industrial ecology, institutionalization.Conclusions. In the context of digital transformation, it is advisable to implement strategic management of industrial ecosystems based on the platform concept. The results of managing an industrial ecosystem with the orchestrator function include enhancing the maturity and integration potential of synergetic interaction in the ecosystem, maintaining a high level of coherence (consistency) between actors at different hierarchical levels, creating long-term value and improving the quality of life.

scholarly journals Industrial synergies from “hidden structures”of knowledge. Towards the foundation of industrial ecosystems.

2020 ◽  
Vol 11 (16) ◽  
pp. 91-110
Author(s):  
Eduardo Aguiñaga
Keyword(s):  
Circular Economy ◽  
Potential Role ◽  
Industrial Ecology ◽  
Symbiotic Relationship ◽  
Industrial Landscape ◽  
Industrial Ecosystem ◽  
Industrial Ecosystems ◽  
The Creation ◽  
Conceptual Research

Industrial strategies based on industrial ecology and circular economy have populated the current industrial landscape. However, these approaches focusing on the creation of symbiotic relationship among industries have beenrelatively insufficiently researched. Although economically and environmentally beneficial, the process of their emergence and development remains unclear. This conceptual research advances the potential role of knowledge in the creation of symbiotic linkages through a qualitative theoretical literature research. The result is a conceptual framework combining different theoretical streams. I conclude that by using absorptive capacity constructs coupled with the principles of industrial ecosystem framed under social network analysis, the genesis of industrial ecosystem can be unearthed.

Use of the designer's experience in systems of computer-aided design and artificial intelligence

2021 ◽  
pp. 89-95
Author(s):  
А.И. Гайкович ◽  
С.И. Лукин ◽  
О.Я. Тимофеев
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Sets ◽  
Computer Aided Design ◽  
Design Tool ◽  
Design System ◽  
Design Problems ◽  
General Arrangement ◽  
Computer Aided ◽  
A Chain ◽  
Aided Design

Процесс создания проекта судна или корабля рассматривается как преобразование информации, содержащейся в техническом задании на проектирование, нормативных документах и знаниях проектанта, в информацию, объем которой позволяет реализовать проект. Проектирование может быть представлено как поиск решения в пространстве задач. Построение цепочки последовательно решаемых задач составляет методику проектирования. Проектные задачи могут быть разбиты на две группы. Первая группа ‒ это полностью формализуемые задачи, для решения которых есть известные алгоритмы. Например, построение теоретического чертежа по известным главным размерениям и коэффициентам формы. Ко второй группе задач можно отнести трудно формализуемые или неформализуемые задачи. Например, к задачам этого типа можно отнести разработку общего расположения корабля. Важнейшим инструментом проектирования современного корабля или судна является система ав­томатизированного проектирования (САПР). Решение САПР задач первой группы не представляет проблемы. Введение в состав САПР задач второй группы подразумевает разработку специального ма­тематического аппарата, базой для которого, которым является искусственный интеллект, использующий теорию нечетких множеств. Однако, настройка искусственных нейронных сетей, создание шкал для функций принадлежности элементов нечетких множеств и функций предпочтений лица принимающего решения, требует участие человека. Таким образом, указанные элементы искусственного интеллекта фиксируют качества проек­танта как специалиста и создают его виртуальный портрет. The process of design a project of a ship is considered as the transformation of information contained in the design specification, regulatory documents and the designer's knowledge into information, the volume of which allows the project to be implemented. Designing can be represented as a search for a solution in the space of problems. The construction of a chain of sequentially solved tasks constitutes the design methodology. Design problems can be divided into two groups. The first group is completely formalizable tasks, for the solution of which there are known algorithms. For example, the construction of ship's surface by known main dimensions and shape coefficients. Tasks of the second group may in­clude those which are difficult to formalize or non-formalizable. For example, tasks of this type can include develop­ment of general arrangement of a ship. The most important design tool of a modern ship or vessel is a computer-aided design system (CAD). The solu­tion of CAD problems of the first group is not a problem. Introduction of tasks of the second group into CAD implies development of a special mathematical apparatus, the basis for which is artificial intelligence, which uses the theory of fuzzy sets. However, the adjustment of artificial neural networks, the creation of scales for membership functions of fuzzy sets elements and functions of preferences of decision maker, requires human participation. Thus, the above elements of artificial intelligence fix the qualities of the designer as a specialist and create his virtual portrait.

Hider: A Methodology for Early-Stage Exploration of Design Space

1996 ◽  
Author(s):  
Sudhakar Y. Reddy
Keyword(s):  
Design Space ◽  
Optimization Problems ◽  
Early Stage ◽  
Simulation Models ◽  
Design Tool ◽  
System Level ◽  
Complex Simulation ◽  
Machine Learning Approach ◽  
Detailed Simulation ◽  
And Performance

Abstract This paper describes HIDER, a methodology that enables detailed simulation models to be used during the early stages of system design. HIDER uses a machine learning approach to form abstract models from the detailed models. The abstract models are used for multiple-objective optimization to obtain sets of non-dominated designs. The tradeoffs between design and performance attributes in the non-dominated sets are used to interactively refine the design space. A prototype design tool has been developed to assist the designer in easily forming abstract models, flexibly defining optimization problems, and interactively exploring and refining the design space. To demonstrate the practical applicability of this approach, the paper presents results from the application of HIDER to the system-level design of a wheel loader. In this demonstration, complex simulation models for cycle time evaluation and stability analysis are used together for early-stage exploration of design space.

System Design and Modeling of a Thermally Activated Reconfigurable Wing

2010 ◽  
Author(s):  
Richard Beblo ◽  
Darrel Robertson ◽  
James Joo ◽  
Brian Smyers ◽  
Gregory Reich
Keyword(s):  
Thermal Energy ◽  
High Speed ◽  
Frictional Heating ◽  
Mechanical Analysis ◽  
Design Tool ◽  
System Level ◽  
Morphing Aircraft ◽  
Thermal Actuation ◽  
Short Period ◽  
Reconfigurable Structures

Reconfigurable structures such as morphing aircraft generally require an on board energy source to function. Frictional heating during the high speed deployment of a blunt nosed low speed reconnaissance air vehicle can provide a large amount of thermal energy during a short period of time. This thermal energy can be collected, transferred, and utilized to reconfigure the deployable aircraft. Direct utilization of thermal energy has the ability to significantly decrease or eliminate the losses associated with converting thermal energy to other forms, such as electric. The following work attempts to describe possible system designs and components that can be utilized to transfer the thermal energy harvested at the nose of the aircraft during deployment to internal components for direct thermal actuation of a reconfigurable wing structure. A model of a loop heat pipe is presented and used to predict the time dependant transfer of energy. Previously reported thermal profiles of the nose of the aircraft calculated based on trajectory and mechanical analysis of the actuation mechanism are reviewed and combined with the model of the thermal transport system providing a system level feasibility investigation and design tool. The efficiency, implementation, benefits, and limitations of the direct use thermal system are discussed and compared with currently utilized systems.

scholarly journals Genetic algorithms in computer aided inductor design

2004 ◽  
Vol 23 (3) ◽  
pp. 68-78
Author(s):  
Jean Fivaz ◽  
Willem A. Cronjé
Keyword(s):  
Genetic Algorithms ◽  
Power Electronics ◽  
Computer Aided Design ◽  
Design Tool ◽  
Design Problems ◽  
Characteristic Data ◽  
Computer Aided ◽  
Aided Design

The goal of this investigation is to determine the advantages of using genetic algorithms in computer-aided design as applied to inductors.  These advantages are exploited in design problems with a number of specifications and constraints, as encountered in power electronics during practical inductor design. The design tool should be able to select components, such as cores and wires, from databases of available components, and evaluate these choices based on the components’ characteristic data read from a database of manufacturers’ data-sheets.  The proposed design must always be practically realizable, as close to the desired specifications as possible and within any specified constraints.

Enabling the 2.5D Integration

2012 ◽  
Vol 2012 (1) ◽  
pp. 000254-000267 ◽  
Author(s):  
John Y. Xie ◽  
Hong Shi ◽  
Yuan Li ◽  
Zhe Li ◽  
Arif Rahman ◽  
...  
Keyword(s):  
Thermal Management ◽  
Manufacturing Process ◽  
System Level ◽  
Process Window ◽  
Development Effort ◽  
Management Options ◽  
3D Ic ◽  
Industrial Ecosystem ◽  
Customer Model ◽  
On Chip

3D IC is the viable revolutionary technology that will enable system-level integration, miniaturization, optimal power management, increased data bandwidth, and eventually reduced system cost. Like any breakthrough technologies, it faces many challenges. Design methodology, integration technology, manufacturing process and new industrial ecosystem are the areas of focus. This paper will discuss these challenges and Altera's 3D integration development effort. 2.5D is an intermediate path to true 3D IC using silicon interposer and TSV (Through-Si-Via) stacking. The 2.5D stacking configuration offers different form factor, interconnect path, and thermal management options than monolithic packages, which could help to reduce system level power and thermal management pressure. It offers silicon level interconnect density, low inductive path and wide IO application. However, it's power delivery system (PDN) could be the bottleneck for the system to perform at the intended bandwidth and speed. Thus, the whole system, IC-Interposer-Package-PCB, must be considered holistically, and trade off study and compensation mechanism development are needed in such complex system level integration. There are many different 2.5D integration manufacturing flows currently under development. They can be categorized into two major flow options: Attaching interposer to substrate first, which can be called CoCoS (Chip on Chip on Substrate); or attaching device silicon to interposer first, which is also called CoWoS (Chip on Wafer on Substrate). The major challenges are in the areas of manufacturing process window and yield, thin wafer handling, testability and overall cost of the integration process. ,). This paper will discuss design consideration, manufacturability analysis, Logic/memory devices and silicon interposer interaction, and thermal management to enable the 2.5D integration. System level characterization and correlation with simulations are performed. The challenge of new supply-customer model and industrial ecosystem development associated with 2.5D integration will also be discussed.

Automated Design Tool for Automotive Control Actuators

2020 ◽  
Author(s):  
Cyril Picard ◽  
Jürg Schiffmann
Keyword(s):  
Automotive Industry ◽  
State Of The Art ◽  
Automated Design ◽  
Design Tool ◽  
System Level ◽  
Laptop Computer ◽  
Automotive Control ◽  
Design And Optimization ◽  
Reporting Tool ◽  
The Impact

Abstract Automated design tools are seldom used in industry. Their potential, however, is high, especially in companies mostly active in variant design, where custom tools could help cut down development time in the early stages. The design of geared electro-mechanical actuators for the automotive industry is such a case. These actuators are simple examples of coupled multi-disciplinary systems that can be hard to design, since they need to follow strict specifications in terms of performance and packaging. This paper presents an automated design and optimization tool tailored for such systems based on an integrated modeling approach, multi-objective optimization and an interactive reporting tool. The focus is set on the impact of system-level constraints on the usability by industry of the generated designs. In two case studies, the tool is able to find competitive actuator candidates that are cheaper (−3.6% and −11%) and more compact than similar existing products in less than an hour on a state-of-the-art laptop computer. More powerful options or actuators using different technologies have also been proposed. Compared to optimizations done without system-level constraints, the generated actuators are immediately usable by engineers to get accurate insights into the design problem and promote informed decision-making.

Nested and Simultaneous Solution Strategies for General Combined Plant and Control Design Problems

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Daniel R. Herber ◽  
James T. Allison
Keyword(s):  
Optimality Conditions ◽  
Design Theory ◽  
Control Design ◽  
System Level ◽  
Test Problems ◽  
Design Problems ◽  
Closed Form Solutions ◽  
Solution Strategies ◽  
Solution Methods ◽  
And Control

In this paper, general combined plant and control design or co-design problems are examined. The previous work in co-design theory imposed restrictions on the type of problems that could be posed. This paper lifts many of those restrictions. The problem formulations and optimality conditions for both the simultaneous and nested solution strategies are given. Due to a number of challenges associated with the optimality conditions, practical solution considerations are discussed with a focus on the motivating reasons for using direct transcription (DT) in co-design. This paper highlights some of the key concepts in general co-design including general coupling, the differences between the feasible regions for each strategy, general boundary conditions, inequality path constraints, system-level objectives, and the complexity of the closed-form solutions. Three co-design test problems are provided. A number of research directions are proposed to further co-design theory including tailored solution methods for reducing total computational expense, better comparisons between the two solution strategies, and more realistic test problems.

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