SRF Limited Goes Digital with Datonis for Their Dipping Process
BUSINESS IMPACT
- Availability of real-time data for process optimization and for cutting back on wastage
- Transition to predictive quality and specific fuel consumption
- Correlation of process parameters with quality defects became possible
OUR ROLE
- Establishing a correlation on real-time data between process & quality defects and optimizing specific fuel consumption
The Problem
SRF Could Foresee Value in Real-Time Data Integration of ERP and QMS with the OT Infrastructure
SRF Limited is a multi-business entity and a leading manufacturer of technical textiles, fluorochemicals, specialty chemicals and packaging films. It is one of the early adopters of Industrial IoT (IIoT) and has been driving improvements in product quality by connecting a complex chemical manufacturing process through Altizon’s Datonis IoT platform.
SRF has 15 manufacturing plants in India, Thailand, and South Africa, serving customers all across the globe. This case study covers the initiatives in four connected plants across India, namely, Gummidipoondi, Gwalior, Manali, and Trichy.
SRF wanted to accelerate its IoT-enabled digital transformation by connecting critical processes – from polymerization to dipping – in the manufacturing of technical textiles. This case study delves deeper into our work done in the area of dipping. The team was looking at generating the next level of actionable insights from the OT-IT data lake to eventually reach a state of predictive quality and specific fuel consumption. They were looking at an established industrial IoT partner with technical and solutioning capabilities to achieve the desired outcomes.
The SRF leadership team typically identifies projects with a payback of ~1.5 years, to be able to assess the impact and plan ahead, as in the case of Altizon. The leaders determined key focus areas or use cases and began the implementation for one use case in one plant, moving on to other plants after a successful implementation.
Since SRF has been a tech-savvy organization right from the beginning, they had well-defined expectations from the Altizon partnership:
- Process optimization to avoid rework or raw material wastage
- Specific fuel consumption insights
- Predictive analytics
The Solution
Altizon’s Datonis IoT suite was deployed at SRF with Datonis Edge operating in a fail-safe configuration inside the customer’s network. Datonis IoT platform and MInt were deployed on the cloud. The Datonis IoT API was leveraged to integrate with all dependent systems including ERP and QMS.
Use Cases
Predictive Quality
Perform root cause analysis of parameters that govern process quality using statistical and machine learning techniques.
Specific Fuel Consumption
The production team can analyze the fuel consumption across the dipping process and keep the expenditure in check.
Batch Traceability
Production teams are able to respond quickly to issues by tracing back a part or product through the supply chain to identify the root cause.
Digital Dashboards
Digital dashboards provide real-time insights to the plant head into key KPIs across Quality, Fuel and Energy dimensions.
What’s Next
Having a combination of technology, domain understanding, process improvement techniques and rapid deployment helps ensure a successful IIoT implementation with payback that is predictable and meaningful – as evident in the case of SRF Limited. The team is now exploring condition-based monitoring and productivity optimization through IIoT. They are also in the process of scaling this initiative to other BUs of SRF, such as fluorochemicals business and specialty chemicals business.
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