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Reveal 45% of capacity gains based on self-service analytics

Use Case: Get rid of excel through quick and easy pre-analysis

Customer

Industry:Pharma, mid-sized
Region:DACH, Europe
Process:Produces active pharmaceutical ingredients (APIs) – manufactures various products in batches

Challenge

Increase production capacity and debottleneck batch process in a reactor.

Solution

  • Reveals where the reactor’s idle time is, through showing sensor patterns
  • Offers easily accessible data insights through time series analysis
  • Minimal effort, easy to use tool (included in BCAP)

Benefit

  • Patterns can be used for further analysis, for example identifying spare capacity
  • Follow up Data Science Analysis revealed 45 per cent of non-utilized capacity

Challenge

The customer needed more production capacity, and were aware that capacity was available within the batches and steps - but they did not know where. They also wanted to know why there was so much spread in production time for different batches.

However, process engineers who understand the process are not data scientists, and vice versa. There can be concerns with using data scientists without sufficient information upfront and because of the investment required. Therefore, an easy-to-use tool – better than Excel - that allows process engineers to perform a pre-analysis would be extremely useful.

Solution

A Bilfinger project manager who understood the process but is not a data scientist was given a year’s worth of time-series data for 10 sensors. He easily used point and click to assemble and display a stack of trend graphs, for the four sensors that interested him.

By combining his knowledge of the process with his visual inspection of these graphs, he could make assumptions about the process steps; he confirmed with the customer that these assumptions were correct. He then handed the data to a data scientist, who developed an algorithm that identified that they had about 45 per cent spare capacity. This approach can also be used by the customer’s process engineer.

Use Case: Batch Analysis with Trendminer

„With the help of TrendMiner, we could easily get insights into the duration of the production batches and the steps between them.“

Dr Taede Weidenaar, Senior Consultant Digital Transformation

Customer Benefit

BCAP (Bilfinger Connected Asset Performance Platform) integrates data as a single source to unlock hidden potential. TrendMiner, as one of the benefits of using (licensing) BCAP, facilitated a very easy, low-cost route to providing a first root cause analysis. It allows process engineers to search past process behaviour, and achieve a diagnosis by instantly finding similarities and patterns.

Fast and easy pre-analysis:

  • TrendMiner is used to explore and analyse time series data in a fast and user-friendly way
  • Analysis gives insights into the duration of batches, and of steps within each batch
  • TrendMiner results were the basis for developing the clustering algorithm that identifies the batches and steps
  • Clustering algorithm showed 45 per cent of non-utilized capacity
  • BCAP customers have access to self-service TrendMiner analytics