many companies are still hesitant to make the move toward digitalisation – often due to concerns about complexity and feasibility performance indicators for different control states as well as identify static and sliding friction in servo-valves to optimise maintenance. The result is a hierarchical plant overview – from the high-level management view to details of individual controls – that supports long-term process optimisation and fine-tuning and assists this process with suggestions based on performance analytics, with additional expert reports for critical control loops. Control Performance Analytics is fully automated to provide reliable results at scheduled intervals, delivered via a secure web portal. This approach ensures effective collaboration among the entire team, from the plant manager to the process operator. Control Performance Analytics is provided as a service so that plant operators can select an individual package for a certain time and expand or extend the contract based on the results, to optimise costs; the checks can be performed both before and after start-up to optimise control performance. CASE STUDY 3: REAL-TIME PERFORMANCE MONITORING FOR FASTER, FACT-BASED DECISION MAKING Data transparency and consistency is not just an issue for engineering and lifecycle information. Today’s highly automated plants often feature multiple levels of IT and automation systems, each with its own database for process, production, and business data. Networking these levels of information that exist in the distributed control system, manufacturing execution system, and enterprise resource management system is the first step to support informed decision making during operation. Additionally, the large volumes of data generated process stability and reproducibility. However, a study performed by Control Engineering revealed that in the process industry as a whole, only 50% of control loops of operating plants are optimised. In the fibre industry, the picture is not much different – and often, even worse. In our own assessments, even advanced pulp mills will typically have only 40% of their control loops optimised, with figures for paper mills even lower. In many instances, control loops are set to manual operation, set at initial values for commissioning, and never adapted to operational conditions. As a result, poor control loop performance results in lower overall process control performance, higher consumption of resources, lower process quality, and inefficient and/or unstable processes. Regular inspection and optimisation of control loops during operation is crucial from a technical perspective, as the performance of process control systems will decline if the system is not optimised on a regular basis. In most plants, this decline will result in a performance decrease of 50% every six months if no effort is made (source: Instrument Engineers’ Handbook, Volume 3). The current low rate of optimised control loops is even more astonishing considering the availability of solutions that can assist in the assessment and optimisation of control loops. As part of its SIPAPER portfolio for the fibre industry, Siemens offers Control Performance Analytics services that use the existing control system to check control loop performance. Control Performance Analytics can be used to automatically detect the state of control loops and to calculate key in the process must be managed and translated into meaningful information for the various tasks and organisations in order to effectively support maintenance, production management, and scheduling. A central information and management cockpit, such as provided by XHQ, enables greater production transparency, not only by providing detailed information on processes and products for both management and operation purposes, but also through centralised logging of alarms and events. All operations can be tracked in one system, facilitating compliance with traceability requirements as specified in ISO 9000 and other standards. This easy-to-configure operations intelligence tool can aggregate, relate, and present operational and business data in real time to improve enterprise performance and is scalable from a machine to a mill to a corporate- wide solution to meet individual requirements. MASTERING THE MATURITY CHALLENGE These case studies show that solutions to several production and performance challenges in the fibre industry are readily available, and the technologies mentioned have already been applied in several projects. However, many companies are still hesitant to make the move toward digitalisation – often due to concerns about complexity and feasibility. These concerns are not unfounded, as plants and companies have very different levels of digital maturity depending on their business and installed base. There are modern production lines that are already using Industrie 4.0 principles on a very broad level, WORLD PULP&PAPER 77