Tissue products are essential products for most humans – they are diverse and range from specialised products to commodity ones. Both efficient production and especially logistics are essential in this largely margin-based business.
At the production sites, tissue producers are constantly trying to improve margins by improving equipment availability, optimising product quality, and reducing cost by efficient use of raw materials, equipment, and transportation throughout its value chain.
The name of the game
The overall objective is normally the constant tuning of all parameters to get a minor improvement here and there. This method has historically been used and still is today as tissue producers have done this effectively for many years. The challenge is that the opportunities for efficiency improvement has been reduced as things are more and more efficient already. However, the need for more efficient production has not reduced. On the contrary, the increasing need for sustainable production has pushed the envelope.
Another challenge in tissue operations is the bulky nature of the tissue products which results in a need to be close to consumers in order to have efficient logistic operations. However, the diverse product palette would mean that many different products need to be produced locally and production efficiency combined with wide product portfolio seldom go together. Hence, there is a need for tissue producers to optimise their product portfolios between different production sites. There needs to be a balance between production assets, long and short-term market demand, and logistics costs.
Speed is an important factor in the tissue value chain and value chain actors are striving to minimise storage. This means that a well-functioning supply chain and logistics operation are of key importance. By minimising storage, actors also minimise the capital bound in the supply chain. However, traditional supply chain management and order handling might not be enough to enable right-on-time deliveries. One issue is the time itself as it takes time to handle orders and to load and ship items. Additionally, since there are often several actors involved in the value chain, transparency is an issue as the actors often operate in different system environments. By establishing systems to share information between actors, many hurdles could be removed and would, for example, enable production planning based on consumption in a more direct manner.
An increased level of transparency would also enable better traceability throughout the value chain. For instance, this would make it easy to remove items from the shelves if a serious error has been detected in the production. Even though some producers have traceability in place, it is not to such a high level and is often more manual and not visible in the value chain. However, it is seldom the case that traceability is established before the tissue machine and includes pulps and pulp producers. This is an issue as pulp often is purchased on the spot market and quality may differ between suppliers.
Industrial digitalisation offers a range of new tools to reach new heights of efficiency, sustainability and control
The knight in shining armour – digitalisation
Industrial digitalisation, or Industry 4.0, is often described as a knight in shining armour – a solution for everything – but what is behind the armour and what strength is hidden underneath? To understand the potential that industrial digitalisation offers, it helps to understand that there is much to gain from taking advantage of data that is produced in production processes and logistic chains. Naturally, this is already done today but for any process inthe tissue industry, for instance, it is only a small fraction of all data used. Hence, there is much more data which can be utilised. Another issue is when the data is used and by whom. In many cases the person that needs the data to make a decision does not have the data available when the decision needs to be taken. Also, the amount of data available is part of the challenge. How can we find the golden needle in the haystack and what information is affecting our process? It is here that Industry 4.0 approaches come into play. New technologies like big data, artificial intelligence, machine learning, Internet of things (IoT), 5G and cloud solutions are all part of the new Industry 4.0 toolbox that gives brands new ways to access and use data to meet the tissue industry’s needs.
It is all about data
Considering the challenges that come with data, it is obvious that a lot can be done – things that were not possible only a few years ago. If we start from the beginning, data needs to be generated and the need to connect many things increases. IoT is a term often used. In a scenario where more and more sensors are being used, the demand for new connectivity solutions increases. Suddenly, wired communication and WiFi is not enough and we need to look for mobile connectivity solutions.
The new-coming technology in this area is 5G, which offers the industry a fast, safe, and robust connectivity solution. So, connectivity is important but then we also need to efficiently store and process all the data produced, which is not as easy as it seems. In any process industry there are a lot of operational technology (OT) systems to control and monitor the processes (some examples are PLC, DCS, SCADA).
On top of those, there are manufacturing management systems (MES and MOM) and on the enterprise level we have business-IT systems such as ERP, maintenance and CRM. Today, there are standards that suggest how these systems can be connected. However, a lot of the data is produced in the engineering systems in the design phase of a site. This data is seldom connected to the IT and OT systems, which is a shame as this would cover all information that governs a business and operation. With all the data in one place, new technologies can be used to learn from the data. Different types of artificial intelligence (AI) and machine learning (ML) technologies can be utilised to develop complex models that describe processes and enable prediction of future behaviour.
These technologies are relatively new and still exotic in the tissue industry but are already a commodity in the retail and bank sectors to name a few. In the process industry, these technologies are especially interesting as there is the possibility to change maintenance regime from a preventive maintenance to a predictive maintenance. This in turn makes the whole maintenance more cost efficient and improves equipment availability. They also enabledifferent kinds of process optimisation.
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