Rodrigo José Pires Ferreira

Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis

Multiobjective and Multicriteria Problems and Decision Models.- Multiobjective and Multicriteria Decision Processes and Methods.- Basic Concepts on Risk Analysis, Reliability and Maintenance.- Multidimensional Risk Analysis.- Preventive Maintenance Decisions.- Decision Making in Condition-Based Maintenance.- Decision on Maintenance Outsourcing.- Spare Parts Planning Decisions.- Decision on Redundancy Allocation.- Design Selection Decisions.- Decisions on Priority Assignment for Maintenance Planning.- Other Risk, Reliability and Maintenance Decision Problems.

A decision model for portfolio selection

This study presents one approach to investing in the financial markets using a decision theory point of view, where the main decision is to choose an investment portfolio, based on economic indexes, in order to predict future investments based on historical data, which minimizes the risk involved. The decision model is based on Decision Theory and Bayesian Analysis and the application uses Brazilian financial market data from January 1998 to June 2005 as an input.

A DSS Based on Multiple Criteria Decision Making for Maintenance Planning in an Electrical Power Distributor

This paper presents a real world application that lead to the construction of a decision support system built to support maintenance planning in an electrical power distribution company. The outcome of the DSS is to determine the order of priority in which potential failure repair orders should be conducted. This company-specific problem has been structured and is similar to that of most electrical power distribution companies, since this company has a complex distribution network with different types of customers which leads it to considering different criteria such as income losses, the probability of service interruptions, national regulation criteria, and so forth. There is a specific budget for potential failure repair orders, while functional failure repairs are not modeled at this managerial level since once the service should not be interrupted and involves long term planning. During periodical inspections the entire distribution network is inspected and a database with all this data is maintained. Thereafter, the potential failures in the distribution network are converted into maintenance orders which typically amount to more than 4 times the annual sum allocated for potential failure repairs budget. After having structured the problem, a DSS was built to support maintenance planning that will result in an annual maintenance plan based on the company´s strategic criteria and national regulations.

Selection of Inspection Intervals Based on Multi-attribute Utility Theory

In the context of complex equipment, inspection has an important role to play in maintaining operations at a suitable performance. In fact, for this kind of system, failures are not immediate. Therefore, the concept of delay time is very useful as a two-step failure process, as a basis for constructing inspection models. Another aspect worth noticing is the fact that, in practice, when the decision-maker decides on the time between inspections, he/she takes different aspects into account in a non-structured way. This happens because the majority of inspection models deal with the problem using an optimization approach, where only one aspect is considered. So, the main contribution of this article is to put forward a multicriteria decision model in order to aid maintenance planning. This model takes the decision maker’s preferences into account, as well as, the most important aspects, when considering setting the inspection intervals for periodic condition monitoring, and which are the cost and downtime associated with the inspection policy.

Decision support system for location of back-up transformers based on a multi-attribute p-median model

Facility location is a theory developed to support decisions about where to place strategic resources with low mobility. Determining the best location for a back-up transformer is a relevant example. Thus, this study set out to present a decision support system based on a multi-attribute p-median model. Some hypotheses were assumed through the Multiattribute Utility Theory concept. The back-up transformer locations were indicated and analysed.

Location of Back-up Transformers

This paper presents a multicriteria approach for the determining the proper location for a back-up transformer. Criteria such as: public health, local industrialization, the population of the area, and the distance are considered. When these criteria are taken into consideration, the best location is that which generates the least loss in maximizing the total utility, regarding the location of the back-up in a substation, taking into consideration the benefits of the back-up being in this place.

Decisions on Priority Assignment for Maintenance Planning

This chapter presents multicriteria (MCDM/A) models to classify and assign maintenance priorities in order to allow maintenance planning to be more effective. From traditional maintenance planning techniques such as RCM (Reliability Centered Maintenance), TPM (Total Productive Maintenance) and others, a common aspect of these techniques is the definition of maintenance priorities, based on a criticality classification for RCM, for example. As maintenance planning has to satisfy multiple objectives, such as availability, maintainability, detectability, safety and reliability besides cost, the maintenance manager is a decision maker (DM) who has to establish tradeoff amongst multiple criteria. This chapter presents an MCDM/A model integrated with the RCM structure using Utility Theory principles to include states of nature and the DM’s behavior to risk (prone, neutral and averse) in a decision model based on Multi-attribute utility theory (MAUT). To illustrate situations when a DM has a non-compensatory rationality, and requires an outranking method, a decision model based on ELECTRE TRI is applied. In addition, TPM aspects are discussed in order to emphasize potential MCDM/A problems that may be approached.

Decision on Maintenance Outsourcing

This chapter presents key aspects of multicriteria (MCDM/A) approaches for decisions on maintenance outsourcing regarding maintenance contract, which includes contract selection (e.g. repair contract) and supplier selection. Contract design is a multi-objective task that leads the maintenance manager (or decision maker - DM) to decide amongst a combination of contracts and suppliers’ bids for the service. Given the multiple objective nature of this kind of problem, this chapter presents models that include maintainability, dependability, quality of repair and other aspects besides cost. The decision models presented consider methods such as Multi-attribute utility theory (MAUT) to address compensatory preferences and ELECTRE for preferences that require an outranking method. The DM’s behavior to risk (prone, neutral and averse) is considered by using Utility Theory and Decision theory foundations in order to include the state of nature in decision models. Thus, most of the problems are related to supplier and contract selection, which may be modeled into a single problem when considering all combinations of contracts and suppliers as alternatives, including the possibility of in-house maintenance being undertaken by a maintenance service supplier. Depending on the organization and in how strategic its maintenance function may be, decisions in maintenance outsourcing may be approached in different stages. Thus, a key performance indicator (KPI) for such problems are defined depending on the type of organization, its capabilities and the number of maintenance activities, while the tradeoff amongst strategic objectives is balanced in order to assure the system’s availability.

Preventive Maintenance Decisions

Technological advances in equipment and the increase in process automation has led to the maintenance function having a role in business competitiveness. The contribution of preventive maintenance is discussed, as an important part of this function, with some emphasis on methods for planning replacement, in the sense of time interval of preventive maintenance. The classical optimization approach is used to illustrate the original preventive maintenance problem, thereby enabling insights and discussion of the main features that require the use of MCDM/A approaches for these decisions, and thus considering the multidimensional consequence space. A structured framework to build a multicriteria decision model for supporting the selection of time interval is presented. Two different MCDM/A methods are applied depending on the decision maker’s (DM) preferences. The first illustrates the application of Multi-attribute Utility Theory (MAUT) as an example of compensatory method and; the second details the application of a non-compensatory PROMETHEE method, which considers outranking relations.

Multidimensional Risk Analysis

Accidents involve critical consequences that require an appropriate and efficient form of risk management. A multidimensional risk analysis allows a broader view. MCDM/A approaches enable more consistent decision-making, taking into account the DM’s rationality (compensatory or non-compensatory), DM’s behavior regarding risk (prone, neutral or averse) and the uncertainties inherent in the risk context. This chapter presents numerical applications illustrating the use of multicriteria models in two different contexts: a natural gas pipeline and an underground electricity distribution system. Two different MCDM/A approaches are considered: MAUT (Multiattribute Utility Theory) and the ELECTRE TRI outranking method. In the numerical applications, MCDM/A approach steps for building decision models are presented: identifying hazard scenarios, estimating the set of payoffs, eliciting the MAU function (Multi-attribute Utility function), computing the probability function of consequences and estimating multidimensional risk. Loss functions are introduced in the models to calculate the probability distribution functions over the multiple criteria such as impact on humans, and environmental and financial losses. Therefore, Decision Theory concepts are applied to estimate risk in industrial plants and modes of transportation. Finally, other decision problems related to multidimensional risk analysis, using MCDM/A, are considered in different contexts, such as: power electricity systems, natural hazards, risk analysis on counter-terrorism, nuclear power plant.