How intelligent & flexible service process handling will work in 2024
How to energize service process handling with digital twins for more efficiency in order to save time and money
Today, manufacturing companies face the challenge of constantly extending the life cycles of their high-value products which are normally technology-intensive, expensive and reliability-critical requiring continuous maintenance throughout their life cycle.
The goal is to create new benefits for customers and improve the overall design and production of those products using in-service feedback.
In addition, regular maintenance by the manufacturers offers the opportunity to upgrade components (overhaul) and thus increase the efficiency of a product after recommissioning, to extend maintenance intervals or reduce emissions together with material consumption [1]. It can even lead to new applications for a product.
For example, in November 2022, a Rolls-Royce AE-2100 gas turbine jet engine — utilized in regional aircraft all over the globe — underwent flight tests utilizing hydrogen fuel for the first time after receiving several upgrades. This is a major step in making the aviation sector more sustainable just by overhauling vital components [2].
It can be derived directly from the action plan on Circular Economy to achieve the EU’s 2050 climate neutrality target and to halt biodiversity loss [3].
Gaining market shares through service optimization in highly competitive markets
Sounds like a win-win for all of us? Great! But wait! There are two huge elephants in the room which I haven’t mentioned yet.
Today’s service processes of high-value products are very inefficient due to the division of components into lots and the lack of operating data!
However, the service processes would have to be particularly efficient to keep downtimes to a minimum and save costs. So how can that be?
Sometimes, even if single product components, like turbine blades of a gas turbine, do not require maintenance at a particular workstation, they may still have to undergo the entire maintenance process within a service lot. This results in components being unnecessarily stored at the workplace, leading to increased maintenance time.
Especially in highly competitive markets the efficient maintainability of a product can mean a decisive competitive advantage [1][4].
Usage and operational data are decisive for flexible, individual, and fast service processing
As mentioned before the lack of usage and operational data is a big problem.
Manufacturers today often lose all connection to products and also the operational data after development, production, and delivery to customers. But if the product is returned to the manufacturer for maintenance as part of a defined service cycle, it is usually this operating data that is decisive for flexible, individual, and fast service processing.
As a result, it is not possible to decide in advance whether the repair of a product is worthwhile at all or whether it is better to replace it right away. Therefore at the start of the service, the products have to be dismantled and every individual component has to be manually inspected which again costs time and especially a lot of money even if a product might already be irreparable.
In an article R. Roy et. al. state “due to technological developments such as Additive Layer Manufacturing (ALM), Industry 4.0 and Internet of Things (IoT) […] there is a paradigm shift in our ability to better repair or replace individual components, better understand the health of a product and plan maintenance based on the availability of significantly large volume of data” [1].
With these developments and the resulting upcoming new product-service business models, the manufacturers can receive operation and usage data from their customers and therefore increase the overall service and product quality. The question of whether the collected data belongs to the manufacturer or the customer/user of equipment should be answered when designing the product-service business models.
Such a service business model can look different depending on the type of product and usage.
“Manufacturers could pay customers for providing the usage data, because with the data the manufacturer improves product quality by feeding back retrieved information in the product development process following the example of “Total Cost of Ownership (TCO)” contracts” according to R. Roy et. al. [4].
But whether gaining data by directly buying it from customers will work on a broad scale is highly questionable.
Gaining data through added customer value
Another much easier approach could be to improve the quality of service received by the customer (as “serviceability”) and implement an autonomous maintenance approach to reduce the through-life cost of the equipment and therefore increase customer satisfaction as a manufacturer[4].
By simply providing operational data, overall maintenance downtime can be reduced (Failures can be recognised earlier and repaired in regular service cycles) which saves valuable resources for production and maintenance and again improves productivity.
Sounds like the data problem will be solved due to business interests in one way or another. All that remains now is to make the service processes more efficient for the still reparable products with the lowest possible costs and downtimes. How?
Simply use individual Maintenance Repair and Overhaul (MRO) processes in combination with digital twins for products.
One major reason for using digital twins is that manufacturers can plan MRO processes in a qualified manner during the product development process, even for individual components. This includes cataloguing potential damage and faults in advance and linking repair measures to them for better planning.
Linking operating & service data in the Digital Twin
If you have never heard of Digital Twins I want to give you a quick ramp up.
As part of IoT, the digital twin maps the entire life cycle of a physical component or product. The information, e.g. from the product development process (PDP) or operation phase can then be used in a variety of ways in the service phase during maintenance. In particular, the geometry, model and planning data from the PDP are stored in the corresponding digital twin immediately after production. This data can then be used for the initial diagnosis of the product in service.
In addition, the operating data can be transmitted to the twin via connectors through edge devices and stored for predefined use cases such as e.g., Predictive Maintenance. Furthermore, IoT platforms provide a technical basis for the digital twin by ensuring connectivity to industrial plants as well as integration with participating company-wide systems that are responsible for test planning, quality assessment or repair execution.
But most important, with the Digital Twin it is possible to link operating data from the customer with service data from the manufacturer in a centralized data storage. For this to work, the data must be provided by the customer or acquired by the manufacturer via the new business models already mentioned. After this is ensured, all the necessary data is available for product, production, and process improvements.
Let us now shift our focus to the role of the digital twin in MRO processes and how it can aid in individual service processing for specific components and products. We will explore how these processes work in tandem to achieve optimal results.
Individual MRO processes in combination with Digital Twins
The service process is essentially determined by the three phases: Initial Inspection, Repair Execution and the final Inspection and Test phase after the service has been carried out.
While the repair process is based on the defects from the Initial Inspection phase, the final inspection is again dependent on the repairs conducted on the product. For the individual service of a component, this means that a list of defects is created for each product or component and, based on this, an individual service repair plan and a corresponding inspection and test plan.
It should be noted that for gas turbines the initial inspection is the same for all products of a material master and thus also for all components derived from it and is therefore handled via a standardized inspection plan. The resulting Defect List is also standardized. Each defect consists of
- an inspection zone or inspection point where the damage occurred,
- a defect type that is usually based on a specified catalogue of defects such as “crack”,
- and one or more defect characteristics that describe the properties of the defects, e.g. crack with 6mm length.
Equivalently, the standardized inspection plan includes various inspection operations, each of which can include different inspection steps. Accordingly, each step consists of
- an inspection zone or inspection point,
- a description of the inspection to be carried out,
- one or more inspection characteristics that are to be recorded for a possible defect,
- as well as the measuring equipment and test stations to be used for this purpose.
Each inspection characteristic in turn consists of an inspection criterion (limit such as length < 10 mm), a measured value and a rating or inspection result.
The actual inspection is then triggered by an inspection order, which results in the individual list of defects for each component to be tested. The digital twin serves as a central information hub between test stations and worker assistance systems, storing and making measured values interchangeable.
Service Action Catalogue as the missing link between inspections and repairs
To be able to make the individual service of a component possible in the first place, an important link is still missing, which has not yet been presented.
This link is the so-called Service Action Catalogue (SAC), in which inspection zones, inspection characteristics, and inspection criteria are linked to repair measures for a material master. Depending on the service supplier, different repair measures may be offered in the catalogue for the same test characteristics and test criteria within a zone. Reasons for this can be, for example, that the suppliers do not have the necessary machinery to carry out a specific repair operation.
The processing of the linked repair measures is documented in the form of a so-called standard service work plan, which is created in parallel with the SAC for the material master. The standard service work plan consists of various sub-work plans, each of which contains several work and test operations and may require certain machines and systems.
The SAC and also the standard service work plan are created during service planning as part of the PDP and are subject to a defined and standardised approval process.
While the standard service plan can be copied from already existing templates, the release process for the SAC is much more complex during its qualification process.
How to develop a SAC?
The development process of the SAC can be broken down into four phases until its release. Each phase is completed by the approval of one or more review boards with the participation of different experts.
- In the first phase, the requirements for servicing a material master are determined. In this phase, the expertise of engineers and product managers who are directly involved in the PDP is crucial. After completion of the survey, the technical feasibility will be evaluated by various experts as part of an initial review board and a functional specification will be drawn up.
- In the second phase, a specification sheet is drawn up from this functional specification and a supplier evaluation is carried out. Both activities are also approved by a review board.
- The third phase is the most important. Here, individual inspection zones and possible defect types, including their inspection characteristics are defined and linked to possible repair measures or sub-work plans from the standard service work plan. Both internal repair measures and external measures by suppliers are considered. The resulting service design is approved by another review board.
- In the final phase, the costs for the planned service processing are evaluated and the final catalogue of repair measures is created. Only after the estimated costs and the final design have been accepted by further review boards, the catalog can be released for service processing.
The final catalogue is then imported into a decision modelling tool either in a machine-readable format or as a decision tree. As soon as the standard service work plan has been released, all the prerequisites for individual MRO process handling are met.
But how does individual MRO process handling by using the SAC actually work?
Now let us explore how the service handling works in total in a rough overview.
The MRO process begins with the receipt of a service order. This defines the components to be inspected. Each component is assigned a separate digital twin, if not already available, which is then filled with the customer’s operating data via a request or an import.
During the standardized inspection process, defects are digitally recorded in the twin. After this, the defect list is imported to the decision modelling tool, which already contains the SAC for the respective material master. Based on the defects and their characteristics, the measures required for the repair can then be determined and reported back to the digital twin.
Using this new list of individual measures, the standard service working plan can then be reduced to the individual sub-service work plan in the twin. The resulting individual repair plan is then transferred to the ERP system and converted into a specific repair order for the component in the next step of the process. The repair order schedules individual repair and inspection steps, which are then processed accordingly on the shop floor. The resulting order and operation data are also managed in the digital twin.
Subsequently, the individual inspection and test plan is derived from the repair plan according to the repair measures conducted on the component. This plan is then used for the final inspection before the component is reinstalled in the product or delivered to the customer.
Key takeaways
- The approach allows for flexible and individual handling of MRO processes for individual components through digital twins.
- With individual MRO processes handling efficiency is increased and valuable resources can be saved.
- A development process for a SAC was shown which enables such handling.
- The concept was developed and validated together with a key industrial player in the gas turbine market and will be introduced in the upcoming years.
- With the introduction, the company will secure and increase its market share and make a contribution to sustainability.
Currently, we are working on the implementation of the concept and I will show what this might look like in detail in an upcoming story. So be curious and in the meantime please feel free to contact me for more in-depth insights, questions and other concerns. I am never averse to a well-founded discussion.
Stay tuned for more blog posts on current topics from the world of production, service, digital lifecycle management and sustainability.
The presented concept is developed as one of the central goals of the Maintenance, Repair and Overhaul 2.0 (MRO) EU-funded research project of the Werner-von-Siemens Centre for Industry and Science (WvSC) [5] in which CONTACT Research is taking part.
References
[1] R. Roy et. al. — Continuous maintenance and the future — Foundations and technological challenges, https://www.sciencedirect.com/science/article/pii/S0007850616301986#bibl0005
[2] Flight Global — Rolls-Royce unveils hydrogen test programme using AE 2100 and Pearl 15 engines, https://www.flightglobal.com/farnborough-2022/rolls-royce-unveils-hydrogen-test-programme-using-ae-2100-and-pearl-15-engines/149402.article
[3] EUR-Lex — Document 52020DC0098, https://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1583933814386&uri=COM:2020:98:FIN
[4] Fortune Business Insights — Gas Turbine Market, https://www.fortunebusinessinsights.com/gas-turbine-market-106255
[5] Werner-von-Siemens Centre for Industry and Science, https://wvsc.berlin/en/
About CONTACT Research. CONTACT Research is a dynamic research group dedicated to collaborating with innovative minds from the fields of science and industry. Our primary mission is to develop cutting-edge solutions for the engineering and manufacturing challenges of the future. We undertake projects that encompass applied research, as well as technology and method innovation. An independent corporate unit within the CONTACT Software Group, we foster an environment where innovation thrives.
