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The thermal-processing industry is much more than asset-intensive. The majority of the equipment is critical in ensuring employee safety, temperature uniformity and final product specifications. This article will compare three of the most common maintenance strategies and highlight the advantages and disadvantages of each.
Semiotic Labs, a company based in Leiden, Netherlands, and Germany’s SMS group signed an agreement under which the two companies will cooperate in the field of predictive maintenance. The AI-based technology developed by Semiotic Labs uses electrical signals and the data fingerprint of AC motors and other rotating equipment to monitor and analyze the condition of critical plant assets and enable reliable and early prediction of developing faults. SAM4 operates based on sensors installed directly in the control cabinet – not on the asset itself. This solution is particularly useful for the monitoring of equipment in the metallurgical industry.
Industrial heating equipment manufacturers; engineering, procurement and construction (EPC) companies; and power and process plant owners and operators commonly face the challenge of keeping their fleet, machinery and other assets working efficiently while also reducing the cost of maintenance and time-sensitive repairs.
Zenith Cutter, a manufacturing company based in Loves Park, Ill., purchased an Ipsen TITAN H6 vacuum furnace with 2-bar gas quenching that will be used at its Metkraft facility in Ho Chi Minh City, Vietnam. The furnace has a graphite work zone measuring 36 x 48 x 36 inches with a 3,000-pound load capacity. It is capable of operating at temperatures of 1000-2400°F (538-1315°C) with ±10°F (±6°C) temperature uniformity. The furnace is also equipped with a closed-loop water system and Ipsen’s PdMetrics predictive-maintenance software.
This paper provides an in-depth look at the functionality and benefits of the PdMetrics™ software platform, including its ability to anticipate future furnace problems and reduce unplanned downtime.