NEW YORK
,
January 25, 2022
(press release)
–
DEVICE AND APPLICATION PLATFORM SERVICES, DATA ANALYTICS, AND IOT SECURITY AMONG THE NECESSARY TECHNOLOGIES TO AVOID UNPLANNED DOWNTIME AND IMPROVE OVERALL EQUIPMENT EFFECTIVENESS Pulp and paper producers face twin challenges. First, the gigantic machines converting wood pulp into paper-based products are a single point of failure. Second, the industry is embracing sustainability by the difficult task of incorporating recycled paper into production while retaining the required quality levels. These challenges are fueling investment in process control software and data analytics to avoid unplanned downtime. Global technology intelligence firm, ABI Research finds that this adoption will grow by a 7% CAGR between 2021 and 2030 and result in a US$3.6 billion spend at the end of the decade. “Paper usage is changing with demand for newsprint and printed paper on the decline while sales of tissues and paper-based medical products are rising rapidly. Technology suppliers can help mills plan for adjustments and retain overall equipment effectiveness.” explains Michael Larner, Industrial and Manufacturing Principal Analyst at ABI Research. Overall ABI Research forecasts that pulp and paper mills will be spending US$3.6 billion on digital technologies in 2030. Spending on IoT devices and the supporting platforms that, for example, support efforts to prevent unplanned downtime will be worth US$1 billion in 2030 with spend on data analytics to evaluate and optimize the production processes forecasted to be worth US$370 million. The foundations for the upswing in the flow of data will be investments in connectivity (forecasted to reach US$450 million in 2030) and network services (US$30 million in 2030). While all the technology investments need to be underpinned by robust cyber security, which is forecasted to be the highest growing spending area (CAGR 8.7%), being worth US$120 million at the end of the decade. Technology providers helping mills extract and make sense of data from their machines include AspenTech, dataPARC, Eigen Innovations, Seeq, and Senseye, while Emerson, Honeywell, and MRPeasy look to help mills design their operations. “Paper needs to be smooth and of a consistent thickness to meet customer requirements. In addition, pulp and paper mills can be crippled by unplanned downtime as dust blocks up machines’ filters or the paper breaks as it’s being rolled or moves through the machine. The size of the machinery and speed of production provide important test cases for technology suppliers. To meet these challenges, production facilities will increasingly look to predictive maintenance and quality automation.” Larner concludes. These findings are from ABI Research’s Digitalization in the Pulp and Paper Industry application analysis report. This report is part of the company’s Industrial and Manufacturing research service, which includes research, data, and ABI Insights. Based on extensive primary interviews, Application Analysis reports present in-depth analysis on key market trends and factors for a specific application, which could focus on an individual market or geography. About ABI Research ABI Research is a global technology intelligence firm delivering actionable research and strategic guidance to technology leaders, innovators, and decision makers around the world. Our research focuses on the transformative technologies that are dramatically reshaping industries, economies, and workforces today. ABI Research提供开创性的研究和战略指导，帮助客户了解日新月异的技术。 自1990年以来，我们已与全球数百个领先的技术品牌，尖端公司，具有远见的政府机构以及创新的贸易团体建立了合作关系。 我们帮助客户创造真实的业务成果。 For more information about ABI Research’s services, contact us at +1.516.624.2500 in the Americas, +44.203.326.0140 in Europe, +65.6592.0290 in Asia-Pacific or visit www.abiresearch.com.
* All content is copyrighted by Industry Intelligence, or the original respective author or source. You may not recirculate, redistrubte or publish the analysis and presentation included in the service without Industry Intelligence's prior written consent. Please review our terms of use.
