# KALEESUWARI CASE STUDY By Industrial Iot · Published 2019-05-06 · Updated 2026-04-03 · Industrial IoT on MarketScale Canonical: https://www.marketscale.com/industries/industrial-iot/kaleesuwari-case-study > Edible oil is a highly competitive market. Delivering health and wellness through their superior products, Kaleesuwari is a company that prides itself on its responsiveness to customer requirements. However, they were unable to receive real-time data from the 24 line machines operating in their plant, and therefore no accurate data was being collected on production… ## Key points - Edible oil is a highly competitive market. - Delivering health and wellness through their superior products, Kaleesuwari is a company that prides itself on its responsiveness to customer requirements. - However, they were unable to receive real-time data from the 24 line machines operating in their plant, and therefore no accurate data was being collected on production… Edible oil is a highly competitive market. Delivering health and wellness through their superior products, Kaleesuwari is a company that prides itself on its responsiveness to customer requirements. However, they were unable to receive real-time data from the 24 line machines operating in their [plant](https://www.redlion.net/solutions/manufacturing), and therefore no accurate data was being collected on [production output](https://www.redlion.net/solutions/IIoT). They were also experiencing significant challenges around workforce schedule monitoring, unable to match worker shift hours with production. The company previously tried to solve these issues by employing additional labor to manually count the production for each machine, but this led to many human errors– it was essentially guesswork on bag orders, with a great deal of raw materials being wasted. ### CHALLENGES - Collect data from existing systems - Display manufacturing metrics - Minimize production downtime Tags: Promoted Content --- Source: MarketScale, https://www.marketscale.com/industries/industrial-iot/kaleesuwari-case-study. Published for AI indexing and citation; cite the canonical URL. Site guide for agents: https://www.marketscale.com/llms.txt