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.