Design Decision-making Process Research Articles

Smart optimal design and analysis of civil structures

A recently completed project is described which had as its objective the development of a prototype interactive AI-based software package to assist in structural analysis and design while explicitly treating uncertain risks. The goal is to increase efficiency, fully integrate and partially automate the design decision process by using AI-based methodologies so that a designer can rapidly evaluate and improve an initial design while taking into account multiple conflicting criteria in the presence of uncertain risk. The prototype software package CODA is described which consists of analysis, design evaluation and optimization tools with user-interactive features.

Communication in a Concurrent Engineering Context: Analysis of an Experimentation

Presently, in a company, the design process is more and more distributed and involves many activities which are shared out among different actors. This kind of work organisation requires to perfectly identify and manage the design process decisions and cooperations. In this paper, we propose an approach to identify and evaluate decisional process. At first, we present the organisation of the project and a quantative overview on the cooperations. Then we propose a method based on the graph theory to identify which kind of cooperation exist between actors during the design process. Finally an example shows the interest of this work

Roadway Seasonal Classification Using Neural Networks

The parameter average annual daily traffic (AADT) is an important factor used in transportation planning, design, maintenance, and other transportation decision-making processes. The most commonly used approach for obtaining the AADT of a particular roadway facility is to obtain short-term counts (usually 48 h), apply the appropriate seasonal coefficients (also known as seasonal factors), and compute the AADT. In this study, a thorough discussion regarding AADT parameter, seasonal factor, annual traffic pattern, and road attributes related to roadway systems is presented. The existing approaches for determining traffic pattern—cluster analysis and regression analysis–are reviewed. Subsequently, an investigation of the potential applicability of the adaptive resonance theory 1 type of neural network associated with roadway classification and pattern recognition is given. In the comparative-analysis part of this paper, all three methods are applied to the same database, and the results of each method’s performance are presented. Finally, after discussing the results, the conclusion is made that the presented adaptive resonance theory’s performance for the given problem is superior when compared to the conventional methods. Some thoughts for further research in this area are also presented.

Flexibility and product variety in lot-sizing models

This paper seeks insight into the role of process flexibility and product variety in the capacitated multiproduct lot-sizing model. The variety of the product line is defined in terms of the number of products and the relative value of their demand rate, setup time, and unit cost of production. Process flexibility is defined as a property of operating costs: one process is more flexible than another if an increase in product variety yields a relatively smaller increase in operating costs. In this context, flexibility is seen to depend not only on commonly understood factors, such as setup time and setup cost, but also on the capacity of the machine. The analysis yields new insights and formulas for the evaluation of product mix, process design and process improvement decisions. The approach can be viewed as an exercise in aggregate sensitivity analysis: instead of focusing on variations in individual scalar data, the analysis considers variations in aggregate measures which are themselves defined as functions of the original problem data.

Modelling of the decision process in an advisory system for technological design

The paper presents a proposal for operational design of the technological process in which the machining process is intergrated with the successive stages of the design of particular operations. The decision problems solved in the process constitute a multi-level decision system divided into several subsystems. On the basis of an analysis of the decision-making process in design, the characteristics of information necessary for its realisation have been provided. Hence, a concept of a system of machining process generation has been developed. The concept has been verified through the construction of an experimental design system.

Models for hypertext

Features characteristic of hypertext are no longer the providence of specialized hypertext systems. Interfaces exhibiting the “power of linking” can be found in software ranging from document preparation programs to operating systems, providing users with many new ap proaches to individual and group information management. To take advantage of the new opportunities afforded by this migration, it is important to understand hypertext at representation levels beneath the more superficial aspects of the human-computer interface. Three abstract models for hypertext-representative members of a spectrum of popular formalisms-are presented to provide insight into the meaning and potential of hypertext. Each model represents a different level in the design-decision process necessary for effective hypertext development, and each model plays an important role in development and use of information management software exhibiting hypertext features. Hypertext provides new methods for organizing and presenting information. The technology has been employed to facilitate personal information management, improve use of large information resources, and coordinate complex planning tasks. Support for hypertexts and related systems is motivated by a belief that hypertext can provide more efficient and personalized access to text by complementing the global search techniques of traditional information retrieval systems with focal navigation based on meaningful inter- and intradocument connections or “links” identified by other means. Informally, hypertext is simply a collection of modular text elements and a set of inter- and intraelement relationships that can be ordered in many ways and used to satisfy a broad range of personalized information needs. More formally, hypertext is: (1) a database of text; (2) a semantic net which connects text components; and (3) tools for creating and manipulating this combination of text and semantic net (Conklin, 1987; Rada & Lunin, 1989; Schnase, Leggett, Kacmar, & Boyle, 1988). Hypermedia is hypertext with nontextual elements. Software is said to possess “hypertext func

Linking Product Planning and Process Design Decisions

ABSTRACTManufacturing strategy reflects the goals of the business strategy and directs the manufacturing function in achieving them. In this study, we focus on two decision areas with crucial implications for manufacturing strategy: product planning and process design. Using mathematical programming models as a research tool, we test several conjectures in the manufacturing strategy literature regarding linkages between the two decisions.Our results show that a close integration between these decisions helps control the product offerings, stabilize process requirements, improve process technology choices, and increase net cash flows over time. Using the concept of environmental clusters, we found that a close linkage is more critical when the environment is more complex, less uncertain, and tighter. Based on these findings, we present some managerial implications and suggestions for future research.

Integration of a New Process Into an Existing Site: A Case Study in the Application of Exergy Analysis

This paper presents a case study that demonstrates how exergy analysis can help make intelligent process design decisions in a logical manner. A proposed, new nitric acid plant is to be intergrated into an existing facility wherein a steam system produces part of the facility’s power needs and all of the process steam, at three pressures. The objective is to minimize the expenditure for fuel and power under two scenarios: when the ratio R of power to fuel costs is 2.5, and when the ratio is 4. The procedure used was first to carry out exergy analyses of the three principal subsystems: (1) the process utilization, (2) the existing steam/power generation, and (3) the proposed HNO3 plant. Secondly, improvements of each of these subsystems were developed, independently, by systematically eliminating unnecessary thermodynamic inefficiencies. (For the steam plant and for the nitric acid plant, alone, improved reconfigurations have been presented earlier: Sama et al., 1988, 1989, respectively.) Finally, in this article, further opportunities for reducing inefficiencies, by integration of the three subsystems, were exploited. In the contractor’s original conceptual design with integration, the facility needs to purchase 77 MW of fuel and 2.2 MW of power. Improved designs developed here save equivalent fuel of over 45 MW when R=2.5 and over 60 MW when R=4 (i.e., 4.5 and 6.0 million dollars per year at a fuel cost of $100/kW-yr or $3.35/106 Btu).

Integration of R&M into CAE for product excellence : William I. Henry. Proc. Reliab. Maintainab. CAE Workshop, 9 (1988)

The issues surrounding integrating R&M analysis into CAE systems go beyond the mere inclusion of R&M analysis tools with design tools. Basic cultural changes to the design process are required. Product excellence requires that design for reliable and maintainable systems will be intrinsic to the design decision process. CAE systems employing R&M analysis functions that are integrated with the design tools are not available today. The CAE industry is beginning to work to provide the capability as new process requirements are developed. Both industry and Government need to work together to make it happen. This paper addresses these i ssues and the needs of companies like Boeing to accelerate the development of design decision support systems to produce products with good R&M characteristics. It gives the Boeing status of the integration of R&M-CAE, what Boeing has to accomplish, and the major technical barriers that Boeing is facing. Results of recent technology breakthroughs are described.

Risk‐Based Selection of Monitoring Wells for Assessing Agricultural Chemical Contamination of Ground Water

AbstractMonitoring of water supply wells has long been a responsibility of public health agencies. With the exception of large municipal water supply systems, most monitoring has been bacteriological, and sampling priority and frequency have been governed by the size of the water supply system. Current concerns about the health effects of agricultural chemicals has created a dilemma for public health agencies, because sampling costs for trace organic chemicals are much higher than for bacteriological parameters. A three‐level hierarchical strategy for jointly assessing contamination risk of water supply wells by agricultural chemicals, and prioritizing wells for sampling, is described. At the first level, a determination is made as to data needs and availability, monitoring objectives are defined, and the scope of the monitoring program is established. At the second level, risk or contamination susceptibility factors are identified, and algorithms for quantifying contamination risk as a function of the susceptibility factors are developed. At the third level, the algorithms are calibrated using pilot data, and an optimization scheme for prioritizing additional wells for sampling is developed based on either minimization of the aggregate health risk and risk uncertainty, or on information gained through sampling. The monitoring of Whatcom County, Washington, domestic wells for ethylene dibromide (EDB), a highly toxic soil fumigant whose registration was suspended in 1983 by the U.S. Environmental Protection Agency, is used as a case study for testing of Levels Two and Three of the hierarchy. In the case study, the initial data consisted of EDB concentrations and ancillary data, such as well depth and pumping rate, for 24 wells already sampled. Susceptibility factors were identified, and a Level Three algorithm was used to prioritize the next 10 wells from among 54 additional candidate wells for a second stage of sampling. The sensitivity of the monitoring well selection, and risk‐benefit tradeoff, are evaluated for different monitoring budgets, risk susceptibility parameters, and risk‐benefit tradeoff criteria.SummaryThe design of sampling programs for detection of agricultural chemicals in ground water is a difficult task. A review of ground water pesticide sampling programs that have been undertaken to date indicate that a lack of direction has existed in many past studies. This lack of focus generally has resulted from failure to clearly define sampling program objectives and to relate data collection priorities to those objectives. Even in California, where a very large sampling program for DBCP was undertaken (more than 8000 wells sampled), Holden (1986) reported that due to the lack of specific study objectives, the data obtained were limited in the scope of their applicability. In this paper, a methodology has been described that provides a framework for clear definition of objectives and data needs, enabling efficient design of sampling programs. The framework consists of a three‐level hierarchy. Once study objectives and data needs have been defined at the top level of the hierarchy, specific analytical methods are used (in the second level) to link well contamination probability to certain susceptibility factors and (in the third level) to select wells for sampling in a multistage sampling process.The methodology was applied to a specific problem, the contamination of drinking water in Whatcom County, Washington, by the pesticide EDB. The application study demonstrated the use of available data to estimate the probability of contamination for each well in the study area, and the use of such estimates to guide future sampling as part of a multistage, interactive sampling program. The proposed approach is generally applicable to the problem of ground water contamination by agricultural chemicals. Many pesticides and herbicides are currently of concern because of their potential presence in drinking water. Sampling programs currently being undertaken to study these problems could clearly benefit from structuring of the monitoring design decision process as proposed and demonstrated.

Evaluation of Decision Aids for Training Device Design

Newly developed cost and training effectiveness models are being used by training developers to control costs and to insure systematic training device design. The problem for the user is how to select the appropriate design aid. Unfortunatly, there are no quick objective methods on which to base this selection. The selection decision for a particular application can be made based on three issues. The first issue is how the design aid addresses device instructional and fidelity features. The second issue is how the design aid formalizes the device design decision process. The third issue is to compare the systems on their ease of implementation. Two decision aids are analytically evaluated on their approach to training device design: OSBATS (Optimization of Simulation Based Training Systems), which is in prototype development, and ASTAR (Automated Simulator Test and Assessment Routine), which is ready to be fielded. These decision aids are based on differing theoretical approaches to formalizing training device design. OSBATS's taxonomy of fidelity features relates instructional features to individual tasks. OSBATS contains a tradeoff function which uses historical cost and benefit values for individual features. It uses large amounts of detailed information to drive its algorithms. ASTAR is a management tool which organizes the diverse interests of a design group to address design issues. ASTAR obtains judgments about instructional approach and device similarity for each training objective. ASTAR facilitates communication between members of a design team and insures a consensus on the issues.

Decision Processes for Low Probability Events: Policy Implications

This survey describes the impact of judgements and choices about low probability, high consequence events on the policymaking process. Empirical evidence indicates that normative models of choice, such as expected utility theory, are inadequate descriptions of individual choices. The ambiguity of low probabilities also affects decisions in ways that are not normative. Further, people exhibit biases in judgments about risks and probabilities. These findings have stimulated development of new theories, such as prospect theory and generalized utility theories incorporating attributes such as regret. The authors survey many of these empirical results and explore their implications for policy. They consider the role of information, economic incentives, compensation, and regulation in inducing socially desirable effects through the reframing of outcomes. They suggest that surveys and experiments can help analysts better understand the decision process for low probability events and design more effective public policies.

Computer-aided building design economics: An open or closed system?

The use of economics in evaluating building designs has been proposed by a variety of authors over a number of years (see, for example, Stone, 1966 and Handler, 1970). The basic principles have not changed as reflected in more recent works on the subject of life cycle costs (Haviland, 1977; Marshall and Ruegg, 1980); and a set of generally accepted standards have been promulgated to insure the technical adequacy of life cycle cost procedures (ASTM E917-83). Nevertheless, life cycle cost principles have been slow in achieving acceptance as an integral part of the building design process. A number of reasons for this reluctance have been proposed, including the variability of cost data, forecasting and uncertainty, interactions between the building and its users, and questions concerning the reliability and cost of life cycle cost analysis (Flanagan, 1984). While these arguments all have substantial merit, others (Kelly, 1984) suggest that significant acceptance will occur only when cost evaluation methods are presented to the designer in terms that the designer understands. This paper suggests that there are more fundamental issues involved in the use of economics within the design process. These issues revolve around the notion that building design economics is inextricably tied to a wide spectrum of design decisions involving assessments of both economic as well as non-economic performance issues. Most significant design decisions, it is argued, are made in this extremely rich and complex context. Designers intuitively make “trade-offs” and “cost-benefit” decisions that simultaneously consider many factors. The use of special purpose, stand-alone economic evaluation systems is inappropriate for this type of decision-making. This paper explores the implications of developing a computer-aided design system where economics is an integral, rather than separate, element in the design decisionmaking process.

Objective functions for optimal building design

In this paper, the authors describe 13 investor motivations for initiating a project. Quantitative criteria to measure success in achieving these motivations are listed. One of the these criteria, net present value, is selected as most capable of reflecting key investor motivations. This measure is manipulated to yield a life-cycle costing relationship which can be used as an objective function in the design decision-making process. It is shown that the life-cycle cost equation in its most general form embodies within it a family of commonly used objective functions which describe financial, technical performance and user criteria. Results from a case study in which different objective functions were used are presented.

Economic risks in energy conservation strategies

Uncertainty surrounding the future cost of energy can contribute significantly to the economic risk associated with large building complexes. A methodology for measuring this risk and incorporating it into the design decision-making process is presented. It involves a first and second moment or mean and variance description of life cycle cost. This information may be aggregated into a single number using expected utility theory for the purpose of ranking design alternatives. A case study which deals with various energy conservation strategies for a 30-storey office complex is presented to demonstrate the significance of economic risk for large projects and the dependence of design alternative rankings on the decision criteria selected.

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Condorcet : An unpublished report on hospitals. This report by Condorcet is part of a debate in the Académie des Sciences before the Revolution concerning the replacement of the Hôtel-Dieu. Con-dorcet's propositions are highly original. His hospital planning is presented within the framework of an optimisation problem based on data selected through an empirical process. Instead of a single structure, he recommended breaking up the hospital into smaller neighbourhood units designed by a mul-tidisciplinary team of architects, mathematicians, surgeons, «political scientists » and other specialists. In addition, this is probably the first text to propose community participation in the design decision-making process.

Probabilistic Structural Analysis and Design

Some of the important advantages of probabilistic design procedures are presented and compared with deterministic techniques. The problem of the compounding of hazards is illustrated by comparing a series type of structure with a parallel type of structure. Both structures have the same characteristics from a deterministic viewpoint, but the parallel type clearly is superior to the series type if probabilistic concepts are employed. The specification of material properties in manufacture is clearly probabilistic. These same material properties are specified and treated deterministically in structural practice without regard to the actual properties of the materials. Similarly, real loadings, although probabilistic in nature are treated as deterministic. Analysis and design procedures employ models of loading and response that have little relationship to reality. The design decision process for seismic loading is illustrated using statistical decision theory. The formulation of optimization of decisions under uncertainty is considered.

On design policies for the optimal use of limited resources

Dynamic programming is applied to the solution of a multi-decision problem arising in the long-range design planning of chemical processes. If a resource is available in limited amount, there are alternate means of resource processing and design decisions are to be made at fixed intervals of time, there exists an optimal set of process design decisions which maximize the profit obtained by the exploitation of the resource. Dynamic programming provides an orderly way of determining that optimal decision policy.