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Manufacturing Technology Insights | Tuesday, August 02, 2022
While many pulp and paper companies have been automated for years, they are only now starting to reap the full potential of digital technologies.
FREMONT, CA: In recent years, the pulp and paper industry has digitalized to improve its operational efficiency. This is driven in part by three market trends: Continued price pressure on paper manufacturers as the market for traditional paper products declines, rising demand for paper packaging as a more sustainable alternative to plastic, and rising global demand for tissue products. Machine connectivity, intelligent automation, and advanced analytics enabled by digital technologies enable new levels of productivity in pulp and paper operations by leveraging large amounts of data to deliver better insights. Successful digital innovators are seeing throughput increases of five to ten per cent yield increases of up to five per cent, and significant savings on materials, chemicals, and energy. This represents a USD four billion to USD six billion opportunity for the industry, and the value is attainable right now. Over 25 distinct use cases are already generating value throughout the entire pulp and paper value chain.
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The value of applications is seen that track the real-time material flow from harvester to mill in forestry and logistics to help optimise delivery and planning. Advanced analytics is being used in pulp mills to improve kappa control and fibre yield. Energy optimization, AI-driven root-cause problem solving, and speed optimization increase profit per hour in paper mills. Finally, advanced analytics is driving quality improvements. Create a strategic value-capture road map and install the necessary technology enablers. Companies must articulate clearly the total value potential of digital and how they intend to capture that value over time. A strategic road map helps to anchor the organisation on the sequence of value-capture initiatives as well as the technology enablers that must be implemented (such as sensors, data pipelines, and storage) to capitalise on the opportunity. The goal should be to keep the programme focused on a well-defined business case with specific key performance indicators (KPIs) and to avoid running technology experiments. Create new internal capabilities. New skills and ways of working are required for successful digital transformation. Companies can supplement their workforce with external contractors to begin and build momentum; however, if the digital transformation is to scale and be sustained, these new capabilities must be built in-house. Companies must combine technology and data expertise with the core process and operational know-how to capture the full value and improve implementation outcomes. This necessitates a strong emphasis on hiring and upskilling people in a systematic manner.
Understand how to manage change. The best digital solutions are useless unless they are adopted and used daily in the workplace. To achieve this, organisations must focus on end users of technology, investing time to understand their needs and incorporating their feedback. Both training and reinforcing new behaviours, as well as deploying new applications, require equal focus and attention. Close collaboration between domain and advanced analytics experts was critical to realising the assets' full potential. Instead of relying on mass external recruitment, there was a focus on developing internal capabilities. This included designing and establishing an academy within the organisation that reached more than 20 per cent of the workforce in the first year, ensuring skills were developed at all levels from senior management to line managers, and identifying a group of high-performing individuals to run the centre of excellence, which included data engineering, development, process optimization, and change management.
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