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  • Improve the process efficiency and yield of production facilities while maintaining optimal product quality control.
  • Increase throughput and safeguard asset uptime with continuous intelligence monitoring by integrating IoT hardware and sensor data.
  • Improve visibility and efficiencies within utility resources: water, power and raw materials.
  • Enable insights from raw material through production to finished product as well as outbound shipments and logistics.
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Sectors Plutoshift supports:

breweries sector food and beverage industry icon

Breweries

dairy sector food and beverage industry icon

Dairy

bottled water food and beverage industry icon

Bottled Water

meat sector food and beverage industry icon

Meat Processing

snacks production food and beverage industry icon

Snack Food
Production

sweeteners production food and beverage industry icon

Sweeteners

baked goods sector food and beverage industry icon

Baked Goods

oils sector food and beverage industry icon

Edible Oils &
Extracts

condiments sector food and beverage industry icon

Condiments

soups production food and beverage industry icon

Soups

wineries sector food and beverage industry icon

Wineries

spirits sector food and beverage industry icon

Spirits

juices sector food and beverage industry icon

Juices

carbonated drinks sector food and beverage industry icon

Carbonated Drinks

coffee production food and beverage industry icon

Coffees/Teas

Use Cases

1.
Reverse osmosis membrane productivity
2.
Heat exchanger performance
3.
Refrigeration / cooling systems
4.
Sensor health
5.
Process and equipment performance optimization
1.
Optimizing the frequency of cleans, membrane lifecycle
2.
Model real-time data from heat exchangers to identify performance degradation, predict heat transfer patterns and recommend actions
3.
Predictive maintenance and energy efficiencies
4.
Automatically identifying poor quality sensors
5.
Moving from schedule based to condition based maintenance

Use Cases

Reverse osmosis membrane productivity.
Optimizing the frequency of cleans, membrane lifecycle
Heat exchanger performance.
Model real-time data from heat exchangers to identify performance degradation, predict heat transfer patterns and recommend actions
Refrigeration / cooling systems.
Predictive maintenance and energy efficiencies
Sensor health.
Automatically identifying poor quality sensors
Process and equipment performance optimization.
Moving from schedule based to condition based maintenance

News & Blog

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3 Ways AI Is Energizing The Coffee Industry

By Prateek Joshi: From bean to barista, the global coffee industry is valued at over $100 billion. For a producer, distributor or manufacturer in this massive industry, the use...
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A Day in the Life: Where an Industrial Operator’s Time Goes

Steve is a manager at an industrial beverage plant that produces bottled soft drinks. Accessing, analyzing, and sharing data about the daily performance is an integral part of his...
Beer cans on a manufacturing line

Automation in Manufacturing: 5 Key Business Functions Being Trusted to AI

Artificial Intelligence is an amazing tool available to researchers, industries, and scientists to help solve some of the world’s most complex challenges.
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AI In Manufacturing, 2020 And Beyond

By Prateek Joshi As we continue to dive deeper into Industry 4.0, the state of manufacturing is largely the same as it was several years ago. Recently, I came...

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