Manufacturing is no longer only about creating physical products. Changing consumer demand, the nature of products, the economics of production and the supply chain are also key.

As technology continues to advance exponentially, in the fourth industrial revolution, digital analytics enables a new level of operational productivity. Ubiquitous connectivity throughout supply chains, pervasive sensors and data analytics will drive efficacy and new business models in the manufacturing sector.

These shifts will generate many distinct opportunities:

  • Higher efficiency
  • Enhanced effectiveness
  • Increased predictability
  • Deeper engagement
To compete, manufacturers will have to embrace the opportunities that their data opens to them to increase productivity.

Pre-configured Analytics & Machine Learning systems​

Complexity of adressing business-specifics is often underestimated while technological requirements are overestimated
Lack of understanding in business units on how to utilize Advanced Analytics and Machine Learning
Access to experts with the right set of competencies across different domains
Availability of data at sufficient quality and quantity

Performance Drivers

Predictive MaintenanceCost reduction from minimized number of outages
Manufacturers can avoid long outage periods of expensive machinery by predicting failures and adjusting maintenance cycles accordingly. They will benefit from an increase uptime of their valuable capex.
Demand forecastingCost reduction from optimized production planning and minimized stock levels
Manufacturers can adjust production volume for each product to the actual demand by forecasting it and then adjusting the production planning accordingly. Also, stock levels for supply and products can be reduced in order to reduce storage costs.
Quality assuranceCost reduction from reduced manufacturing errors
Manufacturers can identify reasons for production failures by analyzing sensor data from the involved equipment. They can identify which states of the machines were responsible for the production failures in order to take actions and avoid the manufacturing errors going forward.
Yield optimizationIncreased revenues through higher yield
Manufacturers can identify drivers for high yield in very complex production processes. They can find the optimal set of control levers for reaching the optimal output of the production process.
Energy efficiencyReduced costs by less energy waste
Manufacturers can reduce energy waste by identifying steps in the production process with unnecessarily high energy usage. They can adjust the whole process to minimize energy costs (or to maximize overall profitability).

Next Steps

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