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The papermaking process starts by producing pulp, which is then shaped, pressed, and dried into paper. When sheet breaks occur, they disrupt production unexpectedly and require thorough cleaning and rethreading before restarting. These issues are complicated and confuse even experts because they have multiple, interconnected causes, showing how complex large paper machines are. Although thousands of sensors track the process and generate a lot of data, the problem has persisted for decades despite many attempts to solve it.
The Voith Group is a global market leader in key industry sectors: turbo, hydro, and paper making machines. Voith sets global standards in energy, paper, raw materials, transport & automotive.
Papermaking is an extensive process that begins chemically with the creation of pulp and then moves to a mechanical phase where the pulp is formed, pressed, and dried into paper. During this process, sheet breaks are a major disruption that can affect production without warning. When a sheet break occurs, extensive cleaning and rethreading is required before production can resume.
The complexity of these disruptions baffles even seasoned experts because the causes are varied and often interrelated, reflecting the complexity of paper machines, which are comparable in size to houses.
Thousands of sensors track the process, generating vast amounts of data, yet for decades this has been a serious problem for companies that has resisted all attempts to solve it.
The AI engine behind Process Booster, aivis®, was fed the raw historical process data of a paper production line. The signal of a reflection sensor in the drying section was used as marker to identify the sheet breaks within the data.
aivis® then performed a root cause analysis that revealed several different root cause scenarios, each with its own set of influencing signals and characteristic behavior causing the sheet breaks.
Based on this classification, the process engineer knew what to look for and where the key differences were. This enabled him to interpret and understand the scenarios and develop appropriate countermeasures.
Sheet breaks were reduced by upto 87%, with an average reduction of 55%.Warnings of impending sheet breaks could be issued as early as 60 minutes prior to the incident.
Sheet breaks were reduced by upto 87%, with an average reduction of 55%.Warnings of impending sheet breaks could be issued as early as 60 minutes prior to the incident.
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