In industry data sharing means increasing productivity

Gathering different levels of data on production processes has become easier and cheaper year by year. Opportunities to collect data are available but collecting data alone will not improve a company’s productivity. It is essential to analyze the information, to process the collected data into information and distribute it to the right parties.

“Data sharing cannot be an absolute value in itself, but it is one of the tools for increasing productivity, which is the basis for the future competitiveness of companies,” says Seppo Tikkanen, who leads DIMECC Ltd.’s InDEx program.

InDEx focuses on sharing data and utilizing it in the production network and thus improving productivity. This is done by increasing efficiency or speed or reducing resource demand of the processes.

“The starting point for improving productivity is to identify the current state, because otherwise the objects of improvement and identifying their effectiveness will be left to intuition. As systems, equipment and, for example, delivery networks become more complex, even an experienced person may not be able to identify the best areas for development, especially if the available information is incomplete. The solution for this problem is collected system data that is transformed into knowledge”, says Tikkanen.

Cloud manufacturing portal

InDEx program is funded by the participating companies and Business Finland. The program improves process efficiency through data sharing in a project by, for example, Prima Power, which specializes in sheet metal working machines and systems, and Elekmerk Oy, which specializes in sheet metal mechanics, machining, surface treatments and assemblies. Companies are working together to develop a tool to optimize the ordering and manufacturing process using artificial intelligence. The result is a platform that automates pricing, parts orders, manufacturing scheduling, and bidding.

“The new cloud manufacturing platform will support our customers by automating their manual and time-consuming daily operations, such as calculating quotations and processing orders. The main idea behind the platform is the AI-driven digitalized production flow from order to delivery, which we have been testing together with Elekmerk Oy (HT Laser). By using the new cloud solution, our customers will enter a new era of digital manufacturing and will benefit from improved lead response time and cost savings.”, says Valeria Boldosova, the Digital solutions and strategy developer of Prima Power.

Hoisting rope conditions

Raute is studying the optimization of the manufacturing process with an artificial intelligence-based system that optimizes the use of raw materials and the quality of the end product. The system uses data collected at the beginning of the process, from which the properties of the final product can be assessed on historical data. This information can be used to increase yield and reduce waste and improve the quality of the final product.

New rope

New rope. Image: Konecranes

Konecranes utilizes image data and artificial intelligence to determine the condition and performance of the hoist. The condition of the hoisting rope and the time of replacement are determined on basis of images taken of the hoisting rope. In this way, sudden breakdowns of the hoist and disturbances in production can be avoided. And avoid the cost of unnecessary rope replacements.

“Utilizing a neural network -based algorithm we can identify damage and normal wear in the rope. This information improves safety of the hoist and ensures smooth production by avoiding downtime”, says Research Engineer Roope Mellanen from Konecranes.

Worn rope

Rope at the end of its lifecycle. Image: Konecranes

Sharing data in industry?

Increasing productivity through data processing and sharing opens many opportunities in the industry. This is the day-to-day work of developing companies ’internal processes. In contrast, sharing data outside the organization remains challenging for many reasons.

“There are many examples of selling customer data and open data from public actors, but we all still need good concrete examples of data sharing and its benefits in an industrial environment”, says Seppo Tikkanen.


 InDEx results are presented at the Industrial Data Sharing Day on 10th of November, 2020.


More info about InDEx program 

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