The proper balancing of repair and preventive maintenance activities in the determination of coordinated shipboard allowance lists

1983 ◽  
Vol 30 (4) ◽  
pp. 553-572
Author(s):  
Zachary F. Landsdowne ◽  
Richard C. Morey
Keyword(s):  
Preventive Maintenance ◽  
Maintenance Activities

scholarly journals Incoming Work-In-Progress Prediction in Semiconductor Fabrication Foundry Using Long Short-Term Memory

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Tze Chiang Tin ◽  
Kang Leng Chiew ◽  
Siew Chee Phang ◽  
San Nah Sze ◽  
Pei San Tan
Keyword(s):  
Preventive Maintenance ◽  
Short Term Memory ◽  
Operational Reliability ◽  
Statistical Forecasting ◽  
Work In Progress ◽  
Dependent Behavior ◽  
Proposed Model ◽  
Forecasting Method ◽  
Semiconductor Fabrication ◽  
Maintenance Activities

Preventive maintenance activities require a tool to be offline for long hour in order to perform the prescribed maintenance activities. Although preventive maintenance is crucial to ensure operational reliability and efficiency of the tool, long hour of preventive maintenance activities increases the cycle time of the semiconductor fabrication foundry (Fab). Therefore, this activity is usually performed when the incoming Work-in-Progress to the equipment is forecasted to be low. The current statistical forecasting approach has low accuracy because it lacks the ability to capture the time-dependent behavior of the Work-in-Progress. In this paper, we present a forecasting model that utilizes machine learning method to forecast the incoming Work-In-Progress. Specifically, our proposed model uses LSTM to forecast multistep ahead incoming Work-in-Progress prediction to an equipment group. The proposed model's prediction results were compared with the results of the current statistical forecasting method of the Fab. The experimental results demonstrated that the proposed model performed better than the statistical forecasting method in both hit rate and Pearson’s correlation coefficient, r.

Speeding Maintenance Performance through Time Study

2014 ◽  
Vol 607 ◽  
pp. 860-863
Author(s):  
Nolia Harudin ◽  
Sha’ri Mohd Yusof
Keyword(s):  
Preventive Maintenance ◽  
Equipment Management ◽  
Time Study ◽  
Manufacturing Environment ◽  
Machine Availability ◽  
Actual Observation ◽  
Plant Maintenance ◽  
Plant Operations ◽  
Maintenance Activities ◽  
Maintenance Performance

As more than $300 billion spent on plant maintenance and operations, U.S. industry spends as much as 80 percent of this amount to correct chronic failures of machines, systems, and people. With machines and systems becoming increasingly complex, this problem can only worsen, and there is a clear and pressing need to establish comprehensive equipment management programs that incorporate the diverse considerations that are essential to minimizing risk and lead to effective maintenance. In a production or manufacturing environment, good maintenance engineering is necessary for smooth and safe daily plant operations. This research which was conducted at one of the worldwide well known Semi Conductor Company located at Kedah, Malaysia were drive subject to improve the effectiveness of preventive maintenance activities through lean approaches. Tools such time study, spaghetti diagram and FMEA were the main key tools and concept drive throughout this research. Machine Availability is the indicator used to evaluate the improvement expected for all the proposal took in placed. With the team effort and several proposal were addressed, Machine Availability able to be improved about 0.4% which lead to improvement of weekly preventive maintenance from 4 hours on actual observation to only 1 hours as new target. It also indirectly lead to the improvement of monthly preventive maintenance which may only require 4 ½ hours instead of 5 ½ hours of previous target. The result is currently practiced and team still looking for further opportunity to improve.

Criterion Referenced Measures of Technical Proficiency in Maintenance Activities

1975 ◽  
Vol 19 (4) ◽  
pp. 375-380
Author(s):  
John P. Foley
Keyword(s):  
Measurement Instruments ◽  
Empirical Validity ◽  
Job Knowledge ◽  
Technical Proficiency ◽  
Maintenance Activities ◽  
Paper And Pencil ◽  
Criterion Referenced ◽  
Systems Effectiveness ◽  
Relationship Of

The paper concerns instruments used in the determination of how effeciently maintenance men perform the various tasks of their jobs. Currently, a great deal of reliance is placed on unvalidated job-knowledge tests, theory tests, school marks, supervisors' ratings for such determination. This paper presents a composite of the results of many research and development efforts concerning the empirical validity of such instruments. These results indicate that these measurement instruments have low empirical validity. The limitations of traditional systems effectiveness measures are also discussed. Although job task performance tests (JTPT) have much higher empirical validity, such tests have had very limited use because of their relatively high costs in time, personnel and equipment. As a result of the foregoing findings, the Air Force Human Resources Laboratory (AFHRL) supported a series of efforts to develop better criterion referenced JTPT, and to attempt the development of paper and pencil symbolic substitute tests of high empirical validity. The paper describes the model battery of 48 criterion referenced JTPT, which has been developed to cover all key maintenance activities such as checkout, align/adjust, remove/replace, troubleshooting, test equipment and soldering. During this development many factors were considered including the identification and classification of tasks to be measured, the hierarchal relationship of maintenance tasks, the most effective order of their measurement and the ease of test administration. This battery was developed as a model of JTPT to be used on the job and in training. It was also intended as a battery of criterion tests for the validation of paper and pencil symbolic substitute tests. Batteries of graphic and video symbolic substitute tests were developed and given limited validations. The validation of graphic symbolic substitute tests indicated that the symbolics for all activities, with the exception of soldering, have promise. The paper discusses the requirements for additional refinement and validation for the various graphic tests. An unsuccessful effort to develop video symbolic substitute tests is also mentioned. Suggestions are made for the application of criterion referenced JTPT for the improvement of maintenance efficiency.

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