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Tisar Ltd

Tisar

by David Shusterman

What is it about?

Tisar Ltd. was founded in 1986, with the vision and the need to change the old fashioned ideas and patterns of machinery maintenance.

App Details

Version
1.4
Rating
NA
Size
33Mb
Genre
Business Utilities
Last updated
February 21, 2021
Release date
January 21, 2021
More info

App Screenshots

App Store Description

Tisar Ltd. was founded in 1986, with the vision and the need to change the old fashioned ideas and patterns of machinery maintenance.


The company specializes in Predictive Maintenance services utilising vibration analysis techniques. Tisar is Israel' Predictive Maintenance leading firm providing its services for numerous manufacturing plants with clients including: petrochemical, cement, food, semiconductors, power plants, marine, water, and water treatment, plastic, pharmaceutical, glass, refineries etc.

Its skilled team includes highly experienced machinery engineers.



Target



The PdM system is based on determining the machinery condition as it operates, thus, determining the required treatment long before failure. This allows minimising the number of hours / days machines are not in operation due to maintenance requirements.



Advantage



Analysis of the machinery vibrations provides a reliable indication as to the quality of the operation of the machine and the developments of failure mechanism, wear and tear.


Advanced information about a developing problem in a machine is essential for maintenance planning.



Application



Tisar develops and maintains the implementation of the Predictive Maintenance method:


Database creation


Data collection


Data analysis and reporting



Tisar is committed to perform



Early Alerts on developing abnormalities within the machinery


Identification of abnormal machines


Characterize the abnormality within the machine


Determines Urgency of Maintenance action required


Result



Tisar’ s activity gives the customer the ability to decide on the nature of future activities, regarding maintenance actions and planed shutdowns.


Customer can base his decision on objective information what is the best time to meet minimal lost production - Opex savings.

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