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Find the right level of digitalisation with TRUMPF

Source:International Metalworking News for Asia     Date:2022-04-20
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By: Kathryn Gerardino-Elagio


1650415916493330.jpgModern life is a constant stream of possibilities, and the transformation to a digital world of work must be conceived to comprehensive automation. For this to be successful, it is imperative to get the employees fully onside from a very early stage.


TRUMPF Pte Ltd's mission is to further develop and digitally connect production technology, to make it even more efficient, precise, and future proof. Having mentioned this, the company’s software solutions pave the way to the Smart Factory, allowing them to implement high-tech processes.


International Metalworking News for Asia (IMNA) sat down with Liertz Wolfgang, Head of Smart Factory Solutions, to discuss Industry 4.0 and the trends to watch out for in 2022.


IMNA: For a manufacturing company to implement Industry 4.0 successfully, it demands processes to be intelligent, aware, connected, and responsive. What do you suggest they need to adopt first in order to get there?


Liertz: The most important is for manufacturing companies to adopt awareness first. The Industry 4.0 process requires a new mindset in employees and management. Therefore, it is always best to start transparency on the shopfloor. Many times, production managers would think that there is an OEE (overall equipment effectiveness) of 70% on the shopfloor, but when you measure the real numbers, you will find it much lower, about 40 or 50%.


My first step to commence a digitalised manufacturing is to begin with asking questions and creating transparency. Next is to train management and employees. To continuously improve on all levels of the manufacturing company, it is our best practice to combine methods of Digital Shopfloor Management and a lean management approach.


IMNA: How is TRUMPF positioning itself to provide customers with a comprehensive range of automation products and services?


Liertz:  A couple of years ago, we implemented a strong Smart Factory Solutions team in Singapore, which is responsible for South East Asia and supporting our customers in all countries in the region. Additionally, we are also promoting free webinars every month. We want to show our customers that there's a high potential in digitalising the production, which is sometimes much more promising than upgrading to the next better machine.


In these times of pandemic where traveling in South East Asia has come to halt, the social media has grown much more important, including remote webinars and remote customer meetings. We're connecting remotely with our customers to consult them on factory layouts, digitalisation approaches, and continuous improvement. These have been quite a success with some of our first customers.


In addition, I want to share that in April 2022, we will introduce our new software solution Oseon that boosts productivity in sheet-metal companies, so please be sure to update yourself and follow TRUMPF's LinkedIn profile.


IMNA: What advice do you have for other companies tackling digital transformation?

Liertz: My advice would be getting commitment from top management first. We have customers in South East Asia where top management started and orchestrated processes, which included all departments for the whole company. And in these cases, the digitalisation or the change process had measurable success after a year already, this made them also more resilient for going through the crisis. Thus, creating top management commitment is the key success factor.


I read a good article where it said, "Think Big, Start Small, and Move Quickly." I think this is the critical part. Think big, yes, have a big vision; but don't expect it to happen tomorrow. Start small and analyse exactly what the problem is right now and untangle it. Move quickly ahead.


IMNA: What are some of the upcoming manufacturing trends that you anticipate in 2022 and what are you providing to help companies as they face the ever-changing manufacturing landscape?


Liertz: Clearly the biggest driver is sustainability. Now the question for our partners and customers is how to become more sustainable and more productive, as well as profitable and sustainable at the same time; and very often the solution is the same. Cost reduction is the focus of many companies, not just in economically challenging times. Therefore, the first step toward cost optimisation is to create transparency. We create a solid database in collaboration with customers, drawing attention to the relevant parameters.


For example, the biggest cost optimisation in our sheet metal customers’ production is saving on raw material. Reducing raw material is our customers' biggest potential for cost optimisation. At the same time, material usage is the biggest driver of CO2 equivalents. Hence, sustainability is really going to be much more important in the future. What we can do from TRUMPF side is to disrupt the work of a production manager. There's an excess of data around a production, which can be analysed by machine learning algorithms in the cloud to give good direction and decision support for production managers. I think we will see a lot more of these over the next couple of years to support personnel on the ground, and the production to become more sustainable and profitable.


In order to identify the full potential of customisation, data is bundled and analysed using software solutions. This allows you to bring continuous flow to your production. Working alongside customers, TRUMPF develops goal-oriented solutions for sustainable optimisation of processes and implement customer's individual smart factory step-by-step.


TRUMPF will keep launching innovative products and solutions and we will open up our interfaces to collaborate with partners. In the end, it is the most important part to bring the best solutions to our customers. Stay put for our big announcement about Oseon in April 2022, so follow us on LinkedIn, as I said before, and you will not miss any updates from TRUMPF’s smart factory solutions.

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