Seven large process industry enterprises were interviewed in the DigiProcess project in Northern Finland last spring. When these interviews were analyzed further, key areas for process industry digitalisation investments were identified. This blog highlights these key areas to help SMEs and micro-enterprises to develop their offerings for process industry. (The Finnish version of this blog can be read on the Lapland University of Applied Sciences web page [link])
Digitalization sets wide range of challenges and opportunities for process industry enterprises. It also provides great opportunities for technologically advanced and highly skilled SMEs and micro-enterprises to become partners and service suppliers for process industry.
The process industry needs a lot of experts and competencies in various fields of technologies. They tend to focus on their core businesses and -processes, acquiring non-core expertise and services through suppliers and partnerships. Large process industry enterprises have traditionally collaborated with large suppliers and acquired large entities from them. Changes are taken place in this area. Cooperation and development of digitalisation capabilities have been increasing with SMEs and micro-enterprises over recent years. Partnerships and co-development projects will be started with SMEs and micro-enterprises, as long as they will provide high technological know-how, agility, and flexibility that meets the needs of the process industry.
Key areas of process industry digitalisation investments
In order to maintain competitive advantage, the large process industry enterprises have invested in research and development in the key areas of digitalisation through different projects and pilots. Based on the interviews, following key areas for process industry digitalisation investments were identified:
Large process industry enterprises typically have their own data platform in cloud. Supplier companies providing digital services are usually expected to use these cloud data platforms instead of their own platforms. Supplier companies are expected to have ability to import e.g. their data or application to the cloud platform according to the settled requirements.
Data platforms are the basis for developing data analytics and machine learning. Data platform development is related to the data analytics, data management, usability and reliability. Large enterprises are looking for different solutions to enhance their capabilities and competitiveness of production processes.
Based on the interviews, one of the most developing key areas among the process industry enterprises were data analytics and its various guiding models as well as predictive and prescriptive analytics in production processes and applications. With the help of analysis and machine-learning models, process data can be processed into understandable form through visualizations.
Data analytics support decision-making and guide actions, i.e. creates a review of situation and highlights anomalies from the production processes. The development of proactive and guiding analytics in production processes will be taken forward and e.g. it improves process reliability, process and maintenance optimisation, proactive maintenance, and failure prediction. This helps enterprises to reduce unplanned downtime of production processes.
Data analytics can be used with e.g.:
- prediction of failures e.g. based on neural network models
- predictive and guiding analytics e.g. for predicting line breaks
- advisory service for quality maintenance
- Identifying causes and effects of deviations from the data mass
- reliability-centered sensing and analytics.
Artificial Intelligence (AI)
Within the interviewed enterprises the use of an AI is in early stage. It has been tested and it will be invested in the coming years. AI has been used, among other things, to automate routine tasks, where repetitive and monotonous work will be managed by using e.g. software robotics. Resources could be freed up to perform other necessary tasks.
Interviewed enterprises have also planned to identify the areas where elements of machine learning and artificial intelligence could be utilized. One large enterprise has had discussions and plans about the implementation of an AI-assisted supply chain and introduction of an AI-assisted work planning process.
AR and VR
The key developing areas of digitalisation of large enterprises are Augmented Reality (AR) and Virtual Reality (VR). Application development has been done together with small businesses. Large enterprises have created development plans for the future.
In general, large enterprises are in the early stages of utilizing AR and VR technology. Applications are usually based on commercial technology. Large enterprises can use AR / VR, for example, for personnel safety training and job orientation.
Robotics, machine vision, and the digital twin
Robotics, machine vision, and the digital twin emerged in a few interviews. One enterprise will be investing in robotics as one of its major key areas. The enterprise is planning to test autonomous flexible robots in the future.
Large process industry enterprises are considering various machine vision solutions together with larger supplier companies. Based on the interviews, the enterprises plan to launch investments related to machine vision applications. Those applications support quality management as well as process control and management. The intention is to invest in production lines for basic applications and more advanced machine vision applications.
With the help of larger supplier companies, large enterprises are considering the development and utilization of digital twins. They wish to have a digital environment where a process is possible to simulate and compare the ongoing process in the digital world and the real production process. The purpose is to help operators and to provide predictability to the production process.
Changes in the operating environment and remote location require investment in remote connections and -controls as well as autonomous production. Large enterprises want to be at the forefront of technology utilization.
Digital, autonomous, and automated solutions can be critical for certain types of enterprises to stay profitable. Autonomous production development is progressing and for this reason, there must be advanced technology. Some of the machines are already operated remotely, but development efforts and investments are needed to achieve autonomous production.
In order to stay at the forefront of digital development expertise and resources are required. Large process industry enterprises have invested internally in various development activities and pilots. Micro- and small enterprises as well as large supplier companies have supported this development work and produced various solutions based on the needs of large process industry enterprises.
The technological development of large process industry enterprises and the development of new technologies and the experiment of new technologies open the door to capable micro- and small enterprises. All in all, this is an opportunity for micro-enterprises and SMEs with high technological know-how, agility, and flexibility to meet the needs of the process industry. Large industry enterprises have invested in different key areas of digitalisation in recent years and will be investing in more when technology is developed and is mature enough.
Main contact and inquiries:
Leena Parkkila, Project Engineer, Lapland University of Applied Sciences, firstname.lastname@example.org
Jani Sipola, DigiProcess Project Manager, Lapland University of Applied Science, +358 50 316 7677, email@example.com