Fuzzy Logic Application and Condition Monitoring of Critical Equipment in a Hydro Power Generation Company

In Hydropower generation company, the focus was on making use of the reliability-centred maintenance (RCM) principles in relation to expert systems in order to optimize maintenance of power generation assets at HPGC station. The researchers realised that in order for CBM to come out clearly, it is critical to do the RCM first. Naturally, the ageing equipment demands a paradigm shift in maintenance strategies in order to guarantee continuity of supply and meet the ever-growing stakeholder requirements. Increase in customer demand has worsened the situation. There is need to improve the overall equipment effectiveness (OEE) from the current 60% to the world class 85%, using the same old equipment in order to retain customer satisfaction.

Fuzzy Logic Application in Improving Maintenance in a Mining Company (PMC)

At a platinum mining company, the research was based on the root cause analysis technique. The objective was to determine the major causes of failure of the pebble crusher, to estimate between the major crusher failures and provide suitable solutions that included the optimization of the crushing circuit. Major failures were investigated including the breaking of the main shaft, bearing failure, and also entry of tramp iron in the crushing chamber. In solving these problems, analysis of stresses was done using solid works 2015, and condition monitoring techniques were applied using MATLAB 2015 to investigate the development of the crack in the shaft. The results showed that EN 19 has better physical properties than EN 9 and EN 26. EN 19 was recommended for the construction of the main shaft. Crack detection prediction by using MATLAB can be complemented and validated by the use of non-destructive testing.

Fuzzy Logic Application in Improving Maintenance in a Beverage Manufacturing Company

Fuzzy logic approach was done on a beverage manufacturing company focusing on the bottle washing process. The main problem is that the pneumatic valve of the bottle washer that controls the discharge of clean bottles sometimes sticks or fails, which results in significant loss of production since this is a bottleneck operation. The main causes of failure were found to be the temperature and pressure, which often fell outside the required ranges, and minor contributions to failure due to moisture and abrasive particles. In order to solve this problem, a model reference adaptive fuzzy controller was designed for the pneumatic valve using the MATLAB software. The model reference adaptive control (MRAC) system consists of the reference model that has the desired output of the system. The error resulting from the difference between the actual system output and that of the reference model is executed by the fuzzy logic controller (FLC). The simulation of the behaviour of the valve in response to the reference model was done using Simulink.

Fuzzy Logic Application and Condition Monitoring of Critical Equipment in a Thermal Power Generation Company

The final case study application was at a thermal power generation company. In large-scale industrial applications, the controlling and optimization of the parameters must be done efficiently and effectively so as to attain smooth operation of the plant. In this research, the main control parameters in the boiler were identified as coal flows, temperatures in the combustion zone, air-to-fuel ratio and ash content, that is, the percentage of ash in raw coal, and mineral content. These parameters are monitored to avoid clinker formation in the super heater tubes of the boiler. Condition-based maintenance (CBM) approaches were used to monitor the boiler parameters. Fuzzy logic was applied in the monitoring of these parameters.

Methodological Approaches on Fuzzy Logic Applications in Selected Companies

The chapter is based on fuzzy logic approaches to machinery failure analysis. Six companies and organisations were used as model validation case studies. At a platinum mining company, the research was based on the root cause analysis technique. The objective was to determine the major causes of failure of the pebble crusher, to estimate between the major crusher failures, and to provide suitable solutions that included the optimization of the crushing circuit. The second application was done on beverages manufacturing companies focusing on the bottle washing process. The third company used a reactive and firefighting maintenance strategy which resulted in frequent catastrophic breakdowns, ever increasing maintenance costs, and long, unplanned plant shutdowns. The fourth was done for a hydropower generation company. The dynamic characteristics of these systems are nonlinear and difficult to predict. The fifth case study application focused on the water gate control and avoidance of its failure. The sixth and final case study application was at a thermal power generation company.

A New Technology of Fuzzy Logic in Machinery Monitoring

This chapter is based on fuzzy logic approaches to machinery failure analysis. Six companies and organisations were used as models for validation case studies. An introduction to fuzzy logic is done in this chapter of the book. As part of this book, it explains the marriage of condition-based maintenance (CBM) in artificial intelligence (AI) specifically using fuzzy logic as a subset of machine intelligence. The idea is to make the machine think intelligently like a human being. The International Standardization Organisation (ISO) has now set up a committee of condition monitoring and diagnosis of machines. Many manufacturing companies are pushing their production equipment for every ounce of capacity while, at the same time, trying to cut their overhead costs. This has put a strong emphasis on the importance of quality maintenance services used to care for systems. Service and maintenance are becoming essential for companies to sustain manufacturing productivity and customer satisfaction at the highest possible level.

Fuzzy Logic and Condition Monitoring of Machinery Plant Equipment

The development of fuzzy logic in the companies mentioned by the authors is meant to automate the plant adaptively. The goal is to reduce downtimes in the plant, and hence, the framework done by the researchers will solve the problems by making the plant intelligent. Fuzzy logic is human concept, potentially applicable to a wide range of processes and tasks that require human intuition and experience. In computer, truth values are either 1 or 0, which correspond to true/false duality. In fuzzy logic, truth is the matter of degree, thus truth-values range between 1 and 0 in a continuous manner. Fuzzy logic is a method for representing information in a way that resembles natural human communication.

Programmable Logic Controller Using Fuzzy Logic for Water Gate Re-Design and Condition Monitoring for Dams

The research on gate control work presents the concept of regulating the flow of water by controlling the dam gates or shutters using servo-motors in order to manage the dam water level. Water level control and insufficient water supply are the major challenges at the hydropower company (HDPC). The system at this dam site consists of the outlet works tower with four outlet penstocks that collects water to the main discharge outlet. The automation implements the electronic control system that uses the programmable logic controller (PLC) and the optical level sensors to detect water level. For the new design, the power screw hoist mechanism is used to open and close the gate of weight 600N with the efficiency of 35.4% of the square thread screw. The gate takes 160 seconds to travel a vertical distance of 600mm in its guide, to fully open and close the 400mm penstock diameter. Mat-lab Simulink was used to control the electronic system for stability to avoid vibrations and fluctuation of speed.

Expert Systems and Fuzzy Logic

An expert system is a system that employs human experience or knowledge captured in a computer to solve problems that ordinarily require human expertise. They may or may not have a learning component. Expert systems are a branch of Artificial intelligence. Truemper describes an expert system as an intelligent system which in an interactive setting asks a person for information and, based upon the response, draws conclusions or gives advice. Problems tend to be solved using heuristics (rules of thumb) or approximate methods or probabilistic methods which, unlike algorithmic solutions, are not guaranteed to result in a correct or optimal solution. The authors go further to clarify that expert systems usually have to provide explanations and justifications of their solutions or recommendations in order to convince the user that their reasoning is correct.

The Case for Condition-Based Monitoring

Maintenance is the management, implementation, and control of all activities that are meant to restore an asset to its ideal level of performance and availability with a view to meet the company objectives and competitive advantages. Maintenance has a greatest contribution to profits within an organisation. The profitable and competitive environment of today demands full productivity in industries with minimum capital investments. This involves coming up with strategies to maximise the up time and machine reliability, extending the life of both the plant and the equipment through cost-effective maintenance.