De-bottle Necking Polyethylene Plant Due to Butene Shortage: a Multi-attribute Decision Analysis Using SMART

The E.P Company supplies the customers with varieties of polyethylene products, to increase production capacity on the Low Linear Density Polyethylene (LLDPE) film grade, De-bottle necking in Reactor-2 (reactor dedicated to produce LLDPE grade) done by changing the condensing agent from Isohexane to Isopentane. Due to the production capacity and reliability on the reactor-2 increase, the demand for raw material Butene increase as Butene use as commonomer in the reactor-2 production. In other hand the Butene plant production decrease because of reduction of cooling capacity and efficiency, this condition create gap on the supply and demand for the Butene. The study objective to be achieved is to find the best solution to overcome Butene shortage problem to produce LLDPE polyethylene with considering the decision maker consideration and at optimize the cost. To achieve that objective, the SMART (Simple Multi Attribute Rating Technique) apply to enable decision maker to gain and increased understanding of his or her decision problem. To fulfill the gap on the supply and demand for Butene, a value tree is created, divided into two component cost and benefit. The study found that the best option for the company is to import Butene from outside (with the condition the new Butene sphere needs to be constructed). This option is recommended for implementation even thought it has the value of benefit at 2nd place (50.9), since a move to the option at 1st place (68.6) is expensive considering that each point increase in the value of benefits would cost $USD 515,001.4 and at total$ USD 9,115,524/ year. This option also solves the problem, from attributes view

Establishing viable task domains for telerobot demonstrations

A suite of telerobotic tasks has been compiled and assessed for the purpose of selecting viable tasks for near and far term laboratory demonstrations. The primary intent of developing the task is to provide some technical guidelines, with supporting data, for focusing laboratory demonstrations toward application domains that address a wide array of potential telerobot tasks and required technologies. This wide application would then result in a rich technology development environment to meet the broad task requirements of a system such as the Flight Telerobot Servicer. The methodology and results of the telerobot task assessment are described, including a ranking of the final select suite of major tasks. The presented along with guidelines for both interpreting the task ranking results and setting programmatic objectives based on these results. Detailed data about the task candidates and their respective levels of complexity, task primitive actions, and the actual relative measures of task worth as associated with key tradeoff variables such as cost, available research resources, technology availability, and importance to the user community are also presented

An Examination of the Decision Analysis Approach to R&D Portfolios

A portfolio can be defined as “a purposeful combination of items” (Chien and Sainfort 1998). As the topic relates to research and development (R&D) the items in question are technologies, projects or products under consideration for inclusion in a given portfolio. As described by surveys from Cooper et al (1998), companies have widely varying practices for portfolio selection. This thesis examines existing literature to determine the key characteristics of good portfolio and portfolio method. The approach needs to handle multiple objectives, account for project interactions, and address the social aspect of decision making. The resulting portfolio should be aligned with business strategy, balanced, and of maximum value. It introduces general concepts that have been used to select single projects and reviews five specific applications and assesses them against the key characteristics from the literature. After identifying gaps in the current approaches, a comprehensive approach is proposed. This approach would (1) apply multi-attribute decision analysis at the portfolio level, (2) apply constraints for common inputs to cost such as resources, and (3) apply probabilistic methods to account for project interaction. This approach incorporates successful elements from existing approaches and addresses the two areas that are not adequately addressed with current approaches

Sustainable distribution system design: a two-phase DoE-guided meta-heuristic solution approach for a three-echelon bi-objective AHP-integrated location-routing model

This article introduces a sustainable integrated bi-objective location-routing model, its two-phase solution approach and an analysis procedure for the distribution side of three-echelon logistics networks. The mixed-integer programming model captures several real-world factors by introducing an additional objective function and a set of new constraints in the model that outbound logistics channels find difficult to reconcile. The sustainable model minimises CO2 emissions from transportation and total costs incurred in facilities and the transportation channels. Design of Experiment (DoE) is integrated to the meta-heuristic based optimiser to solve the model in two phases. The DoE-guided solution approach enables the optimiser to offer the best stable solution space by taking out solutions with poor design features from the space and refining the feasible solutions using a convergence algorithm thereby selecting the realistic results. Several alternative solution scenarios are obtained by prioritising and ranking the realistic solution sets through a multi-attribute decision analysis tool, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The robust model provides the decision maker the ability to take decisions on sustainable open alternative optimal routes. The outcomes of this research provide theoretical and methodological contributions, in terms of integrated bi-objective location-routing model and its two-phase DoE-guided meta-heuristic solution approach, for the distribution side of three-echelon logistics networks

Web service-based business process automation using matching algorithms

In this paper, we focus on two problems of the Web service-based business process integration: the discovery of Web services based on the capabilities and properties of published services, and the composition of business processes based on the business requirements of submitted requests. We propose a solution to these problems, which comprises multiple matching algorithms, a micro-level matching algorithm and macro-level matching algorithms. The solution from the macro-level matching algorithms is optimal in terms of meeting a certain business objective, e.g., minimizing the cost or execution time, or maximizing the total utility value of business properties of interest. Furthermore, we show how existing Web service standards, UDDI and BPEL4WS, can be used and extended to specify the capabilities of services and the business requirements of requests, respectively.Applications in Artificial Intelligence - Ontologies and Intelligent WebRed de Universidades con Carreras en Informática (RedUNCI

Development of a comprehensive decision making framework for power projects in New South Wales (NSW)

University of Technology Sydney. Faculty of Engineering and Information Technology.In the backdrop of emerging concerns about sustainability, the contribution of electricity generation to sustainability, the complexity of power projects, and the narrowness of existing decision approaches for selecting power projects – this research develops a comprehensive decision-making framework that can be applied to select power projects for meeting future electricity needs in NSW. This framework is based on Multi-Attribute Decision Analysis (Analytical Hierarchy Process). This framework will assist with complex decisions regarding projects typified by multiple objectives, multiple decision makers, multiple attributes, conflicts, and socio-economic concerns. The appropriateness of this framework is established in this research in terms of its ability to assist with project choices (from among several alternatives), to meet medium (2035) and long term (2050) electricity needs of NSW, in a sustainable manner. The backdrop for the application of this approach is provided by five scenarios, representing alternative technological pathways, energy & environmental and socio-political settings. Fourteen attributes, reflecting major areas of concern relating to economic, environmental, technical, and socio-political issues are considered, guided by literature review and expert opinion. The overall ranking for each alternative is developed on the basis of, first, assessing the economic, environmental, and social impacts of the alternatives; second, incorporating decision makers’ (expert) preferences for selected attributes, through a pair-wise comparison of various attributes; next, developing a weighted average across all attributes. These individual scenario rankings are then used to compare alternatives represented by various scenarios. The analysis suggest that, overall, the BAU scenario, representing a continuation of existing trends in generation-mix is likely to be the most detrimental scenario for achieving sustainable outcomes in NSW, as it will result in highest levels of levelized cost, GHG emissions, total waste, air pollution, visual impact, water use, resource (fuel) use, severe accidents; and lowest levels of new jobs, and political and social acceptance. The best option in the medium term (2035) for NSW will be the HR-1 scenario (40% share of renewables, with nuclear), as it will result in the highest levels of new jobs, political and social acceptance; and lowest levels of levelized cost, GHG emissions, total waste, air pollution, resource (fuel) use. The best option in the long term (2050) for NSW will be the HR-2 scenario (80% share of renewables, without nuclear), as it will result in the highest levels of new jobs, political and social acceptance; lowest levels of total waste, water use, severe accidents; and moderate levels of levelized cost, air pollution, water and resource use. It is interesting to note the change of preference from HR-1 scenario in the medium term, to HR-2 scenario in the long term, as informed by trade-offs between various attributes. The above insights clearly demonstrate the usefulness of the proposed framework for making complex decisions about power projects

The Jet Propulsion Laboratory Electric and Hybrid Vehicle System Research and Development Project, 1977-1984: A Review

The JPL Electric and Hybrid Vehicle System Research and Development Project was established in the spring of 1977. Originally administered by the Energy Research and Development Administration (ERDA) and later by the Electric and Hybrid Vehicle Division of the U.S. Department of Energy (DOE), the overall Program objective was to decrease this nation's dependence on foreign petroleum sources by developing the technologies and incentives necessary to bring electric and hybrid vehicles successfully into the marketplace. The ERDA/DOE Program structure was divided into two major elements: (1) technology research and system development and (2) field demonstration and market development. The Jet Propulsion Laboratory (JPL) has been one of several field centers supporting the former Program element. In that capacity, the specific historical areas of responsibility have been: (1) Vehicle system developments (2) System integration and test (3) Supporting subsystem development (4) System assessments (5) Simulation tool development

Publications of the JPL Solar Thermal Power Systems Project 1976 Through 1985

Bibliographical listings are documentation products associated with the Solar Thermal Power Systems Project carried out by the Jet Propulsion Laboratory from 1976 to 1986. Documents are categorized as conference and journal papers, JPL external reports, JPL internal reports, or contractor reports (i.e., deliverable documents produced under contract to JPL). Alphabetical listings by titles are used in the bibliography itself to facilitate location of the document by subject. Two indexes are included for ease of reference; an author index; and a topical index

Robust Sensitivity Analysis for Multi-Attribute Deterministic Hierarchical Value Models

The Air Force\u27s ability to deploy, employ, and sustain operations in forward locations is a key to mission success. An integral part of this strategy is equipment pre-positioning, to include: vehicles, aircraft support, consumable inventory, and munitions. This research focuses on defining and developing a model to aid decision makers with the afloat pre-positioning and deployment of munitions in an effort to ensure that the right weapons are available when, and where needed. This research places a particular focus on the strategic, global pre-positioning of the Afloat Pre-positioning Fleet (APF) in an effort to minimize the overall response time involved with offloading these ships and transporting their cargo to the intended point of use. The model developed in this study is a mixed integer program that was implemented using the General Algebraic Modeling System (GAMS). The model considers the various aspects of pre-positioning (forward operating locations, Standard Air Munitions Packages, and the APF) in order to optimally locate and configure each APF ship. The methodology for this model was tested and verified using precision-guided munitions data for a number of scenarios