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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:

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Breweries

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Dairy

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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

Image of Bridge with fog in the background

Bridging The Gap Between AI Promise and Results: 3 Actionable Steps

By Prateek Joshi: Analyst firms like Gartner and Forrester have been advising their clients and the industry at large for several years about the dramatic changes automation and AI...
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Why Manufacturing Companies Continue to Struggle with AI Implementation Projects

By Prateek Joshi  Manufacturing companies know that Artificial Intelligence (AI) can have multiple business advantages for the frontline team and on the overall bottom line. But despite companies’ best...
Image of the inside of a computer

Industrial Automation: 4 Industrial AI Predictions for 2020

By Prateek Joshi: 2019 was a banner year for AI! Almost every business magazine and tech publication published a deluge of articles about AI and its impact on the...
Image of a cup of coffee next to laptop

AI for Coffee Manufacturing: 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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