#Analytic hierarchy process 3 levels how to#
#Analytic hierarchy process 3 levels update#

The process of the evaluation method has been started from analyzing various factors which are used for designs the decision making structure.It is included with necessary data for consideration of management alternatives design that comprised of the technology, economics, environment, and also related regulations. The novel of this paper is a ﬂexible analytical program that enables decision makers to ﬁnd the best possible industrial waste management solution to complex problems by breaking down a problem into a systematic hierarchy structure among the various levels and attributes. An Analytic Hierarchy Process (AHP) decision structure approaches to measure the relative desirability of disposal alternatives using value judgments as the input of the various stakeholders. Thus, application of AHP/ANP would derive a more reliable and accurate judgement in material selection and their flexibility allows integration with other decision making tools.Ībstract: The objective of this paper is to present an evaluation method that can aid decision to prioritize and select industrial waste management method. As in a case study, flax fibers obtained the highest value (19%) and rank as number one fibers in the selection where tensile strength is the most significant criteria. AHP computes the priority values from pairwise comparison basis and ANP derives the global priority values based on the inner dependency of the criteria. Therefore, a proposed approach is presented in this study by using Analytic Hierarchy Process/Analytic Network Process (AHP/ANP) to prioritize the criteria for material selection of natural fiber composites automotive components. Several factors need to be considered concurrently and dependency among the factors should be evaluated during the judgement. The result shows that area of Serang city with the value 0.231 (23.1%) as the most priority road to be repaired.Ībstract: Material selection of natural fiber for composite based products is an essential process in product design development especially in application of automotive components. To determine the prediction and priority order of road handling, the Analytic Hierarchy Process (AHP) algorithm is used with consideration of damage, traffic, and economic factors as criteria decision.

In case of road damage handling in some areas still found problems that need to be resolved immediately, one of them is the problem of availability of budget that is not comparable to the level of damage of the road is quite a lot required a method to know the order of the road priority should be addressed immediately. Along with the passage of time and the use of the road, the road will suffer damage due to natural factors as well as other technical factors, so it takes serious handling efforts from the local government to maintain excellent road infrastructure for the community. Experimentations and results show competitive performance and highlight interesting research directions.Abstract: Roads are the key infrastructure that is needed to support the smooth transportation to improve the condition of the community economy. Data analytics tools are developed to help manufacturing system Experts define and fine-tune rules, based on rule firing statistics and corresponding context indicators and performance assessment acquired from simulation.

#Analytic hierarchy process 3 levels update#

SP agents use context indicators and performance assessment to activate Expert rules and update AHP preferences and scales before making dispatching control decisions to react to disturbances. A multi-agent discrete event simulation model is used to create a set of normal and disturbed production scenarios. The mechanism is applied to a dispatching problem in an industrial scale assembly process. The control mechanism involves an Analytic Hierarchy Process (AHP) augmented with Expert rules to cope with the limitations of standard AHP in dealing with dynamic problems.

#Analytic hierarchy process 3 levels how to#

This article suggests a PDC approach that enables SPs to learn how to make control decisions to react to disturbances and maintain continuity of operations. Nevertheless, developing Product-Driven Control (PDC) mechanisms that enable Smart Products (SPs) to make control decisions to cope with disturbances is still a complex, open-ended, and challenging problem. In Cyber-Physical Manufacturing Systems (CPMS), numerous distributed control architectures were suggested to make different production entities active with respect to decision-making and control processes, so that they can process information, interact, and make control decisions in an autonomous and adaptive way.