In het kader van ‘successen zijn er om gevierd te worden’ hebben wij het genoegen u hiermee te informeren over de promotie van Bram Westerweel, onderzoeker binnen het TKI Dinalog project SINTAS. De promotie vindt plaats op dinsdag 14 mei 2019 aan de TU Eindhoven, Senaatszaal, Auditorium.
Additive Manufacturing (AM), also known as 3D printing, has some advantages compared to traditional manufacturing technologies. For instance, AM can be used to produce small series of products on short notice, with low setup costs compared to traditional manufacturing. This is especially relevant for expensive technical systems that need spare parts for their upkeep. My PhD research shows that using AM in these so-called service supply chains can have significant financial and operational benefits.
Expensive technical equipment, such as airplanes and weapons systems, usually needs many different spare parts, but only one or a few at a time. Traditional manufacturing technologies, such as milling and turning or injection molding, are not very well suited to provide these spare parts, because they have very high setup costs and expensive tooling that is usually only needed for a single component. AM, on the other hand, does not need any tooling and has very low setup costs, allowing manufacturers to efficiently produce small numbers of spare parts on short notice and close to where they are needed. This theoretically makes AM extremely suitable for spare parts production. I studied how AM can best be incorporated in service supply chains by investigating four scenarios.
The first, simply switching from traditional to additive manufacturing while still producing parts at a central location, yields some benefits but it does not unlock the real value of AM. Instead of producing spare parts in a central location, firms should print spare parts close to where they are needed – the second approach. This can be especially useful in remote locations, where being able to do AM on site allows users to keep their equipment working at lower costs. In these locations, typical emergency shipment methods such as expedites or transshipments are often not very cost effective. Local AM capacity can quickly provide temporary replacements during spare parts shortages. In the short term, we expect that AM implementation will also be successful in other settings where the regular supply mode does not work, or does not work as well. Completely eliminating all inventory from the supply chain (i.e. only starting production after a component has failed), however, is not advisable because on-demand production has waiting time for printing and delivering spare parts. While inventory-free supply chains are an often-mentioned AM hype we show in our third research topic that this is simply too expensive for systems with high downtime costs.
The most successful AM implementations will rely on local AM capacity. This is further supported by our fourth scenario that includes a new intellectual property (IP) licensing concept. Via this new business model, the original equipment manufacturer (OEM) does not make and sell the spare parts but acts as an IP licensor, allowing others to locally produce the spare parts. This could be much more profitable for the OEM. IP licensing would also allow the supply chain to completely decentralize, with traditional mass-manufacturing facilities being replaced with local printing hubs that can simply download component designs from central servers.
My research thus shows how AM can be successfully incorporated into service supply chains. Especially local printing hubs could become very important in the service supply chains of the future. Fortunately, the network of local 3D printing service providers (PSPs) that supplies this local printing capacity is growing rapidly. With the help of this network, OEMs and asset owners do not need to invest in expensive AM capacity and training of specialized operators to make sure they have the spare parts they need. If they want to optimize their component design, though, starting an in-house AM program can help to develop crucial AM process knowledge.