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Manufacturing intelligence framework solves challenges for consumer manufacturing

Manufacturing intelligence framework solves challenges for consumer manufacturing

Consumer goods manufacturers are operating complex supply chains as they strive to predict fluctuating demand while shortening lead times. Manufacturing is experiencing a digital revolution and those who embrace intelligent software solutions that can distribute valuable data from across the enterprise to the right decision-makers will retain an advantage.

Download this white paper to discover how a manufacturing intelligence framework solves challenges for consumer manufacturing companies.

Business intelligence tools – IIoT, edge computing and low code

Business intelligence tools such as IIoT, edge computing and low-code development have numerous applications in enabling intelligent manufacturing, including digital twins, asset management, predictive maintenance, analytics, design and sustainability. If executed properly, this combination of IIoT, edge computing and low-code development can address many manufacturing challenges including operating costs, timelines, manpower, wastage of raw material, obsolescence of finished goods and sustainability.

Solving challenges in business analytics

At the heart of enterprise manufacturing intelligence, business analytics can solve numerous challenges for consumer manufacturers. With the increased use of data analytics, these solutions can enable 360-degree monitoring of the factory floor and present new opportunities for advanced manufacturing, productivity improvement and sustainable operations by reducing real material resources. This data can also help companies understand current market trends, competition and market needs.

Benefits of predictive analytics to consumer manufacturing

Predictive analytics play a major role in assessing one’s own asset performance, throughput and resource consumption. Predictive maintenance also results in the extension of life for machinery or equipment, adding an element of sustainability. Some additional benefits of predictive analytics to consumer manufacturing include:

  • Eliminating idle time for machines not in use
  • Streamlining processes, leading to more machine hours per unit
  • Enhancing the efficiency of assets to decrease energy consumption per hour

Learn more about how manufacturing intelligence is a key component to drive future success for consumer manufacturers with this latest white paper.

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Manufacturing intelligence framework solves challenges for consumer manufacturing

Consumer goods manufacturers are operating complex supply chains as they strive to predict fluctuating demand while shortening lead times. Manufacturing is experiencing a digital revolution and those who embrace intelligent software solutions that can distribute valuable data from across the enterprise to the right decision-makers will retain an advantage.

Download this white paper to discover how a manufacturing intelligence framework solves challenges for consumer manufacturing companies.

Business intelligence tools – IIoT, edge computing and low code

Business intelligence tools such as IIoT, edge computing and low-code development have numerous applications in enabling intelligent manufacturing, including digital twins, asset management, predictive maintenance, analytics, design and sustainability. If executed properly, this combination of IIoT, edge computing and low-code development can address many manufacturing challenges including operating costs, timelines, manpower, wastage of raw material, obsolescence of finished goods and sustainability.

Solving challenges in business analytics

At the heart of enterprise manufacturing intelligence, business analytics can solve numerous challenges for consumer manufacturers. With the increased use of data analytics, these solutions can enable 360-degree monitoring of the factory floor and present new opportunities for advanced manufacturing, productivity improvement and sustainable operations by reducing real material resources. This data can also help companies understand current market trends, competition and market needs.

Benefits of predictive analytics to consumer manufacturing

Predictive analytics play a major role in assessing one’s own asset performance, throughput and resource consumption. Predictive maintenance also results in the extension of life for machinery or equipment, adding an element of sustainability. Some additional benefits of predictive analytics to consumer manufacturing include:

  • Eliminating idle time for machines not in use
  • Streamlining processes, leading to more machine hours per unit
  • Enhancing the efficiency of assets to decrease energy consumption per hour

Learn more about how manufacturing intelligence is a key component to drive future success for consumer manufacturers with this latest white paper.