Manufacturing Analytics

With Industrial Internet of Things (IIoT), manufacturing analytics comes on a very large scale

Already today, the competitive edge is determined by the targeted and timely procurement of valuable information from gigantic large and distributed data sources. This fact applies especially for the production with its distributed organizations and dynamic supplier networks. How can you win this race in the “data universe”? Would you as an entrepreneur have a chance? The answer is: Yes. Manufacturing Analytics is the favored approach here so that in future, organizations of all sizes will get hold of information they need in order to survive in the global competition.

Big Data technologies for industrial companies of different sizes

This is the motto camLine expands its range of services for the future. The data pools of the future will grow by dimensions. The intelligent networking offers you the potential for a decisive information advantage to speed up decisions and to optimize business processes.

As an industrial manufacturer, you can leverage manufacturing analytics for the following objectives:

  • Increase yield and reduce costs
  • Get better insight into own operational processes
  • Make value networks more efficiently
  • Improve productivity
  • Initiate interconnected continuous improvement programs
  • Support innovation

The objectives do not seem to have changed much compared to the past. What is really new here?

Manufacturing Analytics

Our environment has changed and provides data from distributed data sources on a very large scale of how they were not in the past made available. The challenge is to merge these distributed data sources from

  • own organizations (e.g. OLTP, i.e. relevant data from the current production control),
  • supplier networks, and from
  • various channels, especially with respect to customer feedback,

to a gigantic data lake that respects the local data sovereignty but fullfills all conditions to gain targeted high-quality information from the data universe. This is done in three steps:

  • Data Mining
  • Analytics
  • Reporting

This approach is only possible by combining pioneering Big Data technologies with conventional data warehouse strategies. The objective is the development of a Smart Data platform for a straight forward and high-performance information delivery to various output devices, such as smartphones, tablets, or traditional PCs.


Leading through secured information search with Analytics

Reliable projections will help you react to changes in time

camLine offers services in analytics for their industrial application. The mission is to track down so far unknown relationships with the aim to derive secured claims and predictions for the future. With the aid of statistical methods, you can explore functional dependencies and describe them with mathematical formulas, where other modeling approaches might fail; either because they would be too complicated or expenditures for their elaboration would not be justified.

The approach is process-oriented and is a combination of consulting project work, modern IT techniques, software products, and special expertise in the field of statistics. The workflow can be summarized as follows:

Analytics is being offered as a consulting service by camLine:

  • Observe
    Gather and sift data impartially, understand requirements, detect constraints, recognize problems
  • Discover
    Use analytical techniques and track down relationships
  • Describe
    Express dependencies and arrive at reliable statements
  • Assert and predict
    Transfer statements to new situations and predict future behavior with assessments
  • Verify
    Check and rate assertions and predictions on their accuracy
  • Strengthen
    Create a business framework and find advocates to establish new rules
  • Implement
    Induce changes in order to introduce the new rules in your organization
  • Improve
    On the new status quo, scrutinize the findings and check them for potential improvements once again