Equipment manufacturers commonly face the challenge of keeping machinery, and other assets in effective working condition while also reducing the costs of maintenance and time-based repairs.
Considering the aggressive time-to-market for products and services, it’s becoming increasingly important to identify the cause of their possible faults or failures before they occur. Emerging technologies like the Internet of Things, big data analytics, and cloud are enabling industrial equipment, and assembly robots to convey their current status to a centralized server making detection of faults easier, more practical, and more direct.
By proactively identifying potential issues, companies can deploy their maintenance services more effectively and improve equipment up-time. The critical features that help to predict faults or failures are often buried in structured data such as year of production, make, model, warranty details, and in other unstructured data. The latter comprises but is not limited to information from millions of log entries, sensors, error notifications, pressure, current, voltage, odometer readings, and engine power-torque specifications.
By using advanced data analytics, the information derived from such sources can be turned into meaningful and actionable insights for pro-active maintenance of assets to prevent incidents that result in asset downtime or accidents, monitor asset behavior, and tune assets for their peak performance levels. Predictive maintenance is a scientific procedure to forecast when a functional equipment will fail, or even deviate from its normal behavior so that its maintenance and repair can be scheduled before the failure occurs.
The underlying architecture of a preventive maintenance model is fairly uniform irrespective of its end applications. The analytics usually resides on a host of IT platforms, but systematically these layers can be described as:
Data acquisition-by embedding suitable sensors and operational log files.
Data transformation—conversion of raw data for machine learning models
Condition monitoring—offering alerts as per operating limits of assets
Asset health evaluation—generating diagnostic records based on trend analysis if health of an asset has already started declining
Prognostics—generating predictions of failure through machine learning models and estimating remaining life
Decision support system—recommendations of best actions
Human interface layer—making all information accessible in easy-to-understand forms
Failure-type classification, fault diagnosis, failure prediction, and recommendation of relevant maintenance actions are all parts of predictive maintenance methodology.
As industrial customers become increasingly aware of the growing maintenance costs and downtime caused by the unexpected breakdown of machinery, predictive maintenance solutions are gaining traction. The bigger players have already been using this methodology for more than a decade. Today, the technology is mature and modularized so the small and medium-sized companies in the manufacturing sector can also reap its advantages by keeping their repair costs low and meeting initial operational costs for new operations.
While it evidently offers more business benefits than corrective maintenance, predictive maintenance is also a step ahead of preventive maintenance—the maintenance work is scheduled at preset intervals and intended to reduce the probability of failure or the degradation of an asset’s functions.
In addition to the advantages of controlling repair costs, avoiding warranty costs for failure recovery, reducing unplanned downtime and eliminating the causes of failure, predictive maintenance employs non-intrusive testing techniques to evaluate and compute asset performance trends. The methods used can be thermodynamics, acoustics, vibration analysis, and infrared analysis among others.
The continuous development in big data, machine-to-machine communication, and cloud technology has created new possibilities of studying the information emanated by industrial assets. Condition monitoring in real time is viable thanks to inputs from sensors, actuators, and other control parameters. What the stakeholders need is a bankable analytics and engineering service partner who can help them to leverage data science to not just predict embryonic asset failures but to eliminate them and take action in a timely way.
Find below a list of the top
Industrial Equipment And Supplies in Doha, Qatar:
- ORIENTAL TRADING CO WLL
Location: 2ND FLR, ENT 9, ARKAN BLDG, COMM AVENUE, INDL AREA,Phone: 44466333Timings:7.30AM-5.00PM : SAT - THUR Key Personnel:V S Narayanan /MNG DIRV M Mathew /FIN MNGRMURUGAVEL /G M - SALESKRISHNAKUMAR/G M - SERVICERAJAGOPAL/G M - PLANT HIRESunil B K /MNGR - MKTG / CREDIT CTRLRajeev Menon /COMM MNGR - PETROCON ECC WLL
Location: ST 8, NEW INDL AREA,Phone: 44979218Timings:Key Personnel:SHYJU VARGHESE/H O D - SALES - RAPTORS TRADING & CONTRACTING
Location: SHOP 9, BLDG 6, BARWA VILLAGE, AL WAKRAH ( H O ); OFFICE 25, 2ND FLR, BLOCK 55, SAYER BLDG, BARWA COMM AVE, INDL AREA ( BRANCH ),
Phone: 44604564
Timings:8.00-1.00/2.00-5.00
Key Personnel:HUSSAIN TAHHAN, SALES MNGR
MOHD KORKOMAZ, SALES MNGR
- ASSOCIATED TECHNICAL TRADING WLL
Location: 2ND FLR, BLOCK 6, ARKAN BLDG, BARWA COMM AVE, UMM AL SENEEM
,
Phone: 44769910;50811108;50643629
Timings:8.00AM-6.00PM : SAT - THUR
Key Personnel:Safdar Grace, SALES DEPT
JISHNU VALORATH, TECHNICAL DEPT
SHAHJAR ALI, PROCUREMENT DEPT
- ORIENTAL TRADING CO WLL
Location: 2ND FLR, ENT 9, ARKAN BLDG, COMM AVENUE, INDL AREA,
Phone: 44466333
Timings:7.30AM-5.00PM : SAT - THUR
Key Personnel:V S Narayanan , MNG DIR
V M Mathew , FIN MNGR
MURUGAVEL , G M - SALES
KRISHNAKUMAR, G M - SERVICE
RAJAGOPAL, G M - PLANT HIRE
Sunil B K , MNGR - MKTG / CREDIT CTRL
Rajeev Menon , COMM MNGR
- FK TOOLS
Location: SHOP 25, BLDG 7, BARWA VILLAGE, AL WAKRAH ( SHOWROOM ); WAREHOUSE A4, NR LOGISTICS VILLAGE, ABA SALIL ( H O ),
Phone: 44919599 - SHOWROOM;40363777 - H O
Timings:7.00AM-5.00PM
Key Personnel:VISHNU GOPAL, COUNTRY SALES MNGR
- PETROCON ECC WLL
Location: ST 8, NEW INDL AREA,
Phone: 44979218
Timings:
Key Personnel:SHYJU VARGHESE, H O D - SALES
- SHOROOK AL DOHA INDUSTRIAL TRDG CO WLL
Location: BLDG 33, ST 100, ZONE 56, AL BUZWAIR COMPLEX, OPP B M W, AIN KHALED; AL WAKALAT ST 13, ZONE 57 ( INDL AREA BR); BLDG 63, ST 750, ZONE 71 ( UMM SALAL MOHD BR ),
Phone: 44603941 - AIN KHALED;40293065 - INDL AREA;31120101 - UMM SALAL MOHD;70588608 - WHATSAPP
Timings:7.00-1.00/3.00-8.30
Key Personnel:THOUFEEQ A JABBAR, ADMIN DIR
NAJEEB HAMEED, MNGR
- GULF LIGHTS ELECTRICAL ENGINEERING WLL
Location: OFFICE 28, WEST CORNER CENTRE, MIDMAC R / A, SALWA RD,
Phone: 44971333
Timings:7.30-1.00/4.00-7.30
Key Personnel:Sanaullah A R , MNG DIR
Amanullah Abdullah , OPS MNGR
KHALID HURZUK, FIN / OPS DIR
MOHD SALIM, B D M
SHRAVAN, PROJS MNGR
GAURAV, OFFICE MNGR
- RESQ TRADING & SOLUTIONS WLL
Location: OFFICE 1, 2ND FLR, BLDG 219, AL EMADI C-22, D RING RD,
Phone: 40416701
Timings:8.00AM-5.00PM
Key Personnel:NAQEE HUSSAIN, C E O
MUFADDAL TAJ, TECH HEAD
- AATLAS AL AALAM ( WORLD ATLAS TRDG CO WLL )
Location: Villa 48, Opp Doha Clinic, Frij Al Nasr,
Phone: 44981555;44981666
Timings:7.30AM-5.00PM : SAT-WED 7.30AM-2.00PM : THUR
Key Personnel:Naser Jamil Said , Mng Partner
- AATLAS AL AALAM - WORLD ATLAS TRADING COMPANY
Location: ,
Phone: 44981555
Timings:
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HEAVY EQUIPMENT & SPARE PARTS
Find below a list of the top products suppliers of
Heavy Equipment & Spare Parts in Doha, Qatar:
- A - Z
- - AEROQUIP
- - AL AFSAN TRADING
- Cargo Lashing Belts, Webbing Slings, Seat Belts, Warning Lights, Cabin Fans. Gasket Sheets - AMMANN
- Asphalt Plants, Concrete Plants, Vibratory Plates, Walk - Behind Compactors, Add - On Compactors, Trench Rollers, Rammers, Single Drum Rollers, Tandem Rollers, Pneumatic Tire Rollers, Asphalt Pavers, Genuine Spare Parts & Services - ANL
- Brake Pads, Brake Shoes
- APOLLO FLEET
- All Kinds Of Equipment Rentals & Transport - ARMSTRONG
- Dirt Rollers, Compactors, Asphalt Paving Equipment - ASHOK LEYLAND
- Heavy Duty Diesel Engines & Spare Parts - ASTRA
- Heavy Duty Trucks, Rigid / Articulated Dumpers, Heavy Haulage Vehicles - ATLAS
- Crane Parts
Related Tags:Heavy Equipment & Spare Parts products in doha qatar |
A - Z Products in Doha Qatar |
AEROQUIP Products in Doha Qatar |
AL AFSAN TRADING Products in Doha Qatar |
AMMANN Products in Doha Qatar |
ANL Products in Doha Qatar |
APOLLO FLEET Products in Doha Qatar |
ARMSTRONG Products in Doha Qatar |
ASHOK LEYLAND Products in Doha Qatar |
ASTRA Products in Doha Qatar |
ATLAS Products in Doha Qatar |
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