DESIGN OF A HIERARCHICAL MULTIOBJECTIVE DECISION-SUPPORT SYSTEM FOR INVENTORY PLANNING AND CONTROL

1986 ◽  
pp. 135-140
Author(s):  
Y. Nishikawa ◽  
J. Nomura ◽  
K. Sawada ◽  
R. Nakajima
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Inventory Planning ◽  
Planning And Control ◽  
And Control

Project Management in Enterprises

2009 ◽  
pp. 2461-2471
Author(s):  
Cezary Orlowski ◽  
Zdzislaw Kowalczuk
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Project Management ◽  
Decision Support System ◽  
Support System ◽  
Project Teams ◽  
Software Project ◽  
Team Members ◽  
Planning And Control ◽  
And Control

The article discusses how the knowledge of management and artificial intelligence can be used for controlling the budgets and schedules ofsoftware projects. The first part of this paper gives an outline of the problems involved in software project management regarding the planning and control of processes and project teams. Next, an overview of changes in management is presented, followed by a description of a method for how these ideas can be used to solve software engineering problems. Consequently, an example is presented of a decision-support system, designed to aid project-team managers in planning and controlling budgets and schedules and helping the team members to adjust.

Plant design and control in food service industry. A multi-disciplinary decision-support system

2018 ◽  
Vol 103 ◽  
pp. 72-85 ◽  
Author(s):  
Alessandro Tufano ◽  
Riccardo Accorsi ◽  
Federica Garbellini ◽  
Riccardo Manzini
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Service Industry ◽  
Food Service ◽  
Plant Design ◽  
And Control

Construction and resource short-term planning using a BIM-based ontological decision support system

2021 ◽  
Vol 48 (1) ◽  
pp. 75-88
Author(s):  
Mehdi Tavakolan ◽  
Sina Mohammadi ◽  
Banafsheh Zahraie
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Construction Projects ◽  
Planning Process ◽  
Resource Planning ◽  
Project Planning ◽  
Short Term ◽  
Planning And Control ◽  
Intelligent Information

The dynamic nature and increasing complexity of the construction projects impose many challenges for project planning and control. As a project progresses, more information becomes available and the level of uncertainty decreases. It can be used to proactively check the validity of the previous decisions and develop revised and more detailed plans for the upcoming activities in construction planning meetings. For this purpose, this study implements ontological knowledge representation and semantic reasoning techniques to propose an intelligent information collection and decision support system framework for short-term collaborative construction and resource planning. Moreover, a new approach is suggested that allows for incorporating resource specifications and limitations, and complex multi-factor constraints in the ontological planning process. The framework was tested based on a real-world construction project and different application cases were discussed. The framework showed a promising performance for analyzing different scenarios and help the planners making informative decisions.

Development of a Decision Support System for Unscheduled Maintenance MRO Component Safety Stock

2007 ◽  
Author(s):  
D. Tsakatikas ◽  
M. Sfantsikopoulos
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Inventory Control ◽  
Support System ◽  
Industrial Production ◽  
Failure Modes ◽  
System A ◽  
And Control ◽  
Functional Components ◽  
Criticality Analysis

The paper presents a methodology for the establishment of the MRO (Maintenance, Repair and Operation) material criticality that is focused on the Industrial Unplanned Maintenance needs. The thus obtained criticality is used to rationalize the efficiency of the Plant MRO-material Inventory. Through an appropriately adapted Top-Down FMECA (Failure Modes Effects and Criticality Analysis) the concept of the Component Dynamic Criticality is introduced and calculated for all the functional components of an industrial production facility. The components are assigned with characteristic code numbers. MRO-material Inventory control is then carried out within the frame of the developed Decision Support System. A case study demonstrates the method. The use of the developed Decision Support System considerably increases not only the efficiency of the Plant MRO-Material Inventory and control of the Unplanned Maintenance Downtime, but also its continuously updated and highly constructive System Dynamic Database of Component Failure Modes and their Effects benefits the Conventional Maintenance Schemes, e.g. Scheduled and/or Predictive Maintenance, as well. MRO-Material Inventory control for rational Unplanned Maintenance Downtime has not been addressed to this date in a systematic way. By addressing this issue the present approach contributes to an increased availability of industrial production facilities and to a better performance of CMMS and/or ERP tools.

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