Technology Evolution Modeling and Decision Making Under Uncertainty

2012 ◽  
Author(s):  
Jonathan L. Arendt ◽  
Daniel A. McAdams ◽  
Richard J. Malak
Keyword(s):  
Decision Making ◽  
Research And Development ◽  
Wind Turbine ◽  
Technology Development ◽  
Modeling Technique ◽  
Technology Evolution ◽  
The Future ◽  
S Curve ◽  
Evolution Modeling

Design is an uncertain human activity involving decisions with uncertain outcomes. Sources of uncertainty in product design include uncertainty in modeling methods, market preferences, and performance levels of subsystem technologies, among many others. The performance of a technology evolves over time, typically exhibiting improving performance. As the performance of a technology in the future is uncertain, quantifying the evolution of these technologies poses a challenge in making long-term design decisions. Here, we focus on how to make decisions using formal models of technology evolution. The scenario of a wind turbine energy company deciding which technology to invest in demonstrates a new technology evolution modeling technique and decision making method. The design of wind turbine arrays is a complex problem involving decisions such as location and turbine model selection. Wind turbines, like many other technologies, are currently evolving as the research and development efforts push the performance limits. In this research, the development of technology performance is modeled as an S-curve; slowly at first, quickly during heavy research and development effort, and slowly again as the performance approaches its limits. The S-curve model typically represents the evolution of just one performance attribute, but designers generally deal with problems involving multiple important attributes. Pareto frontiers representing the set of optimal solutions that the decision maker can select from at any point in time allow for modeling the evolution of technologies with multiple attributes. As the performance of a technology develops, the Pareto frontier shifts to a new location. The assumed S-curve form of technology development allows the designer to apply the uncertainty of technology development directly to the S-curve evolution model rather than applying the uncertainty to the future performance, giving a more focused application of uncertainty in the problem. The multi-attribute technology evolution modeling technique applied in decision-making gives designers greater insight when making long-term decisions involving technologies that evolve.

Uncertain Technology Evolution and Decision Making in Design

2012 ◽  
Vol 134 (10) ◽  
Author(s):  
Jonathan L. Arendt ◽  
Daniel A. McAdams ◽  
Richard J. Malak
Keyword(s):  
Research And Development ◽  
Pareto Frontier ◽  
Evolutionary Process ◽  
Evolutionary Model ◽  
Development Effort ◽  
Technology Evolution ◽  
Curve Model ◽  
S Curve ◽  
Over Time

The potential for engineering technology to evolve over time can be a critical consideration in design decisions that involve long-term commitments. Investments in manufacturing equipment, contractual relationships, and other factors can make it difficult for engineering firms to backtrack once they have chosen one technology over others. Although engineering technologies tend to improve in performance over time, competing technologies can evolve at different rates and details about how a technology might evolve are generally uncertain. In this article we present a general framework for modeling and making decisions about evolving technologies under uncertainty. In this research, the evolution of technology performance is modeled as an S-curve; the performance evolves slowly at first, quickly during heavy research and development effort, and slowly again as the performance approaches its limits. We extend the existing single-attribute S-curve model to the case of technologies with multiple performance attributes. By combining an S-curve evolutionary model for each attribute with a Pareto frontier representation of the optimal implementations of a technology at a particular point in time, we can project how the Pareto frontier will move over time as a technology evolves. Designer uncertainty about the precise shape of the S-curve model is considered through a Monte Carlo simulation of the evolutionary process. To demonstrate how designers can apply the framework, we consider the scenario of a green power generation company deciding between competing wind turbine technologies. Wind turbines, like many other technologies, are currently evolving as research and development efforts improve performance. The engineering example demonstrates how the multi-attribute technology evolution modeling technique provides designers with greater insight into critical uncertainties present in long-term decision problems.

TRIZ Evolution Theory Applied to Man-Made Boards

2013 ◽  
Vol 441 ◽  
pp. 1060-1063
Author(s):  
Hui Ling Yu ◽  
Hao Liang ◽  
De Lin Fan
Keyword(s):  
Life Cycle ◽  
Technology Development ◽  
Evolution Theory ◽  
Niche Space ◽  
Waste Wood ◽  
Term Forecast ◽  
Technology Life Cycle ◽  
S Curve ◽  
Current Stage

Man-made boards often made use of waste wood materials. China is one of the worlds largest manufacturers and consumers of man-made board applications. Application of the law of evolution with a S-shaped curve could contribute essentially to the accuracy of the long-term forecast. This research seeks to determine the current stage and the position on the S-curve of man-made board technology in China on the TRIZ evolution theory and introduce a methodology which combines patent analysis and technology life cycle forecasting to find a niche space of man-made technology development in China.

Getting to the Future

2021 ◽  
pp. 109-128
Author(s):  
Michael K. MacKenzie
Keyword(s):  
Decision Making ◽  
The Political ◽  
Collective Decision Making ◽  
Political Dynamics ◽  
The Future ◽  
Decision Making Processes ◽  
Electoral Cycles ◽  
Shared Futures ◽  
Deliberative Processes

This chapter makes three arguments in support of the claim that we need inclusive deliberative processes to shape the future in collectively intentional, mutually accommodating ways. First, inclusive collective decision-making processes are needed to avoid futures that favour the interests of some groups of people over others. Second, deliberative processes are needed to shape our shared futures in collectively intentional ways: we need to be able to talk to ourselves about what we are doing and where we want to get to in the future. Third, deliberative exchanges are needed to help collectivities avoid the policy oscillations that are (or may be) associated with the political dynamics of short electoral cycles. Effective processes of reciprocal reason giving can help collectivities maintain policy continuity over the long term—when continuity is justified—even as governments and generations change.

scholarly journals THE FUTURE ME, RETIREE: USING THE FUTURE SELF TO ENHANCE LONG-TERM FINANCIAL DECISION MAKING

2018 ◽  
Vol 2 (suppl_1) ◽  
pp. 693-693
Author(s):  
P Lemaster ◽  
A Faber ◽  
K Fernholz ◽  
K Finch ◽  
E Kransvik
Keyword(s):  
Decision Making ◽  
Financial Decision Making ◽  
The Future ◽  
Financial Decision ◽  
Future Self

The Emergence of Democracy: Forces and Counter-forces

2015 ◽  
Vol 50 (3) ◽  
pp. 336-363 ◽  
Author(s):  
Dirk Berg-Schlosser
Keyword(s):  
Decision Making ◽  
Driving Forces ◽  
Empirical Literature ◽  
Democratic Values ◽  
Future Prospects ◽  
The World ◽  
The Future ◽  
Broad Overview

Capitalism and democracy have transformed the world, but not in a harmonious way. This article provides a broad overview of the major driving forces of democracy, its relationship with ongoing socioeconomic developments and some of the countervailing factors. It points to the inherently conflictive nature of democratic procedures and decision-making, but also emphasizes the potentially universal implications of basic democratic values. Against this background, the future prospects of democracy and possible alternatives in the age of globalization are assessed. All this is based, as far as space permits, on the huge body of available theoretical and empirical literature, but also on the author’s long-term preoccupation with this topic and some of his personal views and experiences.

R&D Strategy of the Korean Electric Industry Using a Technology Roadmap(Trm) Approach

2005 ◽  
Vol 277-279 ◽  
pp. 674-679
Author(s):  
Young Eal Lee
Keyword(s):  
Technology Development ◽  
Future Market ◽  
Short Term ◽  
Electric Industry ◽  
Technology Roadmap ◽  
Course Of Action ◽  
Key Technologies ◽  
The Future ◽  
Market Needs

The proper allocation of the limited R&D resources under the restructuring of the electric industry is a primary motivator for this electricity technology roadmap (eTRM) initiative. Because the major interests of CEOs could be the short term profit of their company under the competitive electric industry, it would wrong of them to cut back on the long term R&D budgets which make it impossible to develop all the technologies. Therefore, we should select and support only the favorable and competitive technologies to meet the future market needs using the TRM approach with the concept of "Selection and Concentration." This study aims at defining the key technologies basis from the forecasts of what is possible or likely to happen in the future and planning the course of action for the technology development in the electricity field in Korea. The selected technologies could be the candidates for the mid and long term R&D program supported concentrically by the Electricity Industry Infrastructure Fund.

Economic Decision Making and Risk Management

2019 ◽  
Vol 8 (1) ◽  
pp. 34-58
Author(s):  
Brian J. Galli
Keyword(s):  
Decision Making ◽  
Operations Management ◽  
Corporate Management ◽  
Business Decisions ◽  
Business Operations ◽  
Economic Decision Making ◽  
The Future ◽  
Business Entities ◽  
Definition Of

The definition of long-term objectives in corporate management as well as means of achieving them is often associated with uncertainty. The reason for this is apparent: managers in corporate entities cannot predict all circumstances, whether positive or negative, that is likely to occur in the future. Management during the decision-making process must be able to make informed decisions given the existence of insecurities and uncertainties in the course of business operations. Management must, therefore, take into account the risks that might occur in the future. As a result, this article aims at discussing the risks affecting corporate entities. The paper also defines and analyzes the risks, thus explaining how business entities can tackle them through making informed business decisions.

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