Business Analytics in production

Reduce waste and optimise production

Challenge:
A pharmaceutical manufacturer wants to reduce the proportion of damaged tablets. Until now, quality checks have been carried out by means of random visual inspections. Any defective tablets had to be sorted out manually.

The solution:
Business Analytics evaluates images from high-speed cameras in real time. Defective tablets are thus detected before packaging. Manual rechecking is no longer necessary. Data analysis enables optimal machine settings.

Benefits:
The reject rate fell, as did personnel costs. New machine settings also reduced wear and tear and maintenance requirements on the production line.

Complex logistics under smart control

Challenge:
An international logistics company wants to provide major customers with an online platform for supply chain risk management. The data should enable delivery tracking and provide key figures for failure probabilities.

The solution:
Business Analytics combines data from over 30 sources in a cloud application. Customers can link their business applications to the cloud, enabling them to use real-time tracking and identify delivery delays at an early stage.

Benefits:
Competitive advantages through real-time tracking information and rapid identification of delivery bottlenecks. The data also enables the optimisation of supply chains.

Better quality with less wear and tear

Challenge:
A paper manufacturer produces paper in various types and thicknesses. The machines should always run with optimal settings. The objectives are top quality, minimisation of changeover times and reduction of maintenance requirements.

The solution:
Business Analytics uses data from machine sensors and production management (paper type, print run, etc.). This determines the optimal settings for each production job. At the same time, wear and tear is predicted and service appointments are calculated according to demand.

Benefits:
High quality thanks to perfect machine settings. Maintenance costs fell by over 20% thanks to demand-based servicing. Changeover times were also reduced.

Identifying trends and occupying markets

Challenge:
Long-term customer requirements must be incorporated into product development at an early stage. For sales, the marketing mix, sales channels and ordering methods must be defined and optimal pricing calculated.

The solution:
By analysing competing products and trends on social media platforms, must-haves can be identified and the features of your own product can be designed accordingly. Pricing is calculated across the entire product life cycle.

Benefits:
Reduced risk of missteps in product planning. More efficient marketing with less wastage. Margin optimisation through dynamic pricing from market launch through the product lifecycle to market exit.

All raw materials always in the right place

Challenge:
An industrial company with multiple locations wants to reduce the costs of purchasing and storing raw materials without jeopardising the production chain. This is because the complex just-in-time manufacturing process must continue to run smoothly.

The solution:
Business Analytics combines internal production data with external factors to determine demand forecasts. At the same time, raw material prices and storage costs are taken into account. This ensures that the required raw materials are procured as cheaply as possible.

Benefits:
Both purchasing and logistics costs are reduced, as is the need for storage space. Planning processes have been automated, thereby reducing personnel costs.