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Control and automation key to successful plant operation


Plant automation systems like distributed control system (DCS) have been isolated from the traditional IT domain due to various issues like different technology stacks, perceived security risks, non-standardized and fragmented approach to OT deployment as opposed to a more standardized approach to IT systems.


By Annie Mathew, CIO, Mother Dairy Fruit & Vegetable

Plant automation systems like distributed control system (DCS) have been isolated from the traditional IT domain due to various issues like different technology stacks, perceived security risks, non-standardized and fragmented approach to OT deployment as opposed to a more standardized approach to IT systems.

Mother Dairy Fruit & Vegetable wanted to integrate its IT and OT environment for augmenting operation efficiencies at the plant level. The solution that looked at was plant automation. Over a three month period since the project went live, it has resulted in myriad business benefits for the company.

OT systems typically support real-time production requirements and an analytical view of the data was required by the Production team. Considered as a golden opportunity to break traditional barriers between IT and OT systems; bridging OT and IT makes operational data more widely accessible and can lead to strategic planning based on actual operational history – while still maintaining the sanctity of operational systems.

Over the previous year, an initiative was commenced to capture real-time operational data and monitor and analyze process parameters to assess impact on product quality. The primary goal of the project was to bring visibility into operational process parameters which impact product quality and fetch data out of a controlled ecosystem and make it available beyond OT domains to the quality assurance and R&D functions.

Plant automation has significantly increased sigma levels of our plants by reducing temperature variations. Visibility has increased several folds as product traceability reports are now generated real-time. Milk recirculation times have reduced by almost 50 percent.

Going forward, IoT devices will be deployed across outsourced manufacturing plants to integrate the data into the ‘Historian’ to generate consolidated and comprehensive dashboards across all plants at a central level.

Use of predictive analytics on the plant parameters to conduct pre-emptive maintenance and prevent breakdowns is also planned; so as to provide real-time mobile alerts and dashboards to factory managers for remote monitoring.

Plant automation is essential for both pro-active measures and rapid reaction to any condition which requires input. While critical in a business where perishable food products are produced, it is imperative for all manufacturing entities in today’s day and age.

Governments have long dreamt about ending of world hunger. However, in reality as many as one-ninth (around 800 million) of the global population of over 7 billion go hungry each day, with 33 percent of the food produced for human consumption wasted every year.

According to India FoodBanking Network, India is home to the largest undernourished and hungry population in the world: with 15.2 percent of India’s population is determined as undernourished and 194.6 million people go hungry every day.

Can such a sorry state of global food chain be set right with appropriate use of digital innovation? Is it possible for big data analytics to turn this dream into reality?

Data to the rescue

There are huge amounts of data that few can glean much out of, without analytics software. Big data analytics can help bring order to the chaos, which in turn could have a direct impact on food production or curb food wastage. For example, cutting post-harvest losses in half can produce enough food to feed a billion more people, as per a McKinsey report. If more data were readily accessible, growers might find systematic approach to fix local hunger issues.

Precision agriculture, which uses big data analytics, aerial imagery, sensors, etc., to observe, measure and analyze the needs of individual fields and crops rather than take a one-size-fits-all approach to farming in a region or cluster of fields, may be an answer. Scientists at the University of Illinois Champaign, for instance, are using supercomputers to pilot an effort that would collate satellite pictures, crop-yield data, market information, pest infestation data and precision agriculture, in a search for patterns and common threads. According to EY, real time wireless sensors can monitor the storage conditions of perishable food as it is transported, and transmit this data to clients to alert them if things are going wrong.

Many companies are building technologies to help reduce waste across the supply chain, from farming and distribution to restaurants and home-cooking. For example, Irish startup Food Cloud matches retailers that have food that might ordinarily go to waste with charities that have the means by which to transport the food, as well as connections with needy people who can use the food.

Large non-governmental organizations are using data analytics to become more efficient in raising and allocating funds, forecasting trends and planning campaigns.

From restaurant scraps, to grocers disposing of imperfect produce, to spoiled food—it’s probably a stretch to say that big data will bring an end to hunger and feed the entire world. However, with such trends there is every reason to believe that by the appropriate application of data compilation and advanced analytics, we are in a better position today to foresee unwanted consequences.

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