Contract processors are faced with a multitude of options as to how they can drive forward digitalization in their own operations. The considerations often revolve around similar questions: What is the best way to start digitization? What are the benefits of this or that technology for my business? The topic usually remains abstract, which limits its transferability to your own company. In order to make the topic of digitalization more accessible and practical and to relate it to the day-to-day work of contract finishers, the article uses an example order to look at individual stages of digitalization from quotation to delivery and explain the background.
The aim is not to present an ideal digitized electroplating shop, but to show the possibilities. Every company has its own requirements, which must be taken into account individually in order to derive the greatest possible benefit from digitalization; the aim of the article is to explain tools for this in a practical way.
Possible procedure for evaluating digitalization measures
Before looking at the digitized order process in detail, the question of the benefits of digitization - and how these outweigh the costs - must first be asked. Various tools are available to help answer these questions. However, especially with a complex topic such as digitalization, it is clear that these analyses are time-consuming and not always meaningful. Nevertheless, it is worth taking a brief look at the theory in order to outline possible methods and procedures for weighing up the introduction of digitalization measures in your own company.
Symbolic illustration of some aspects of digitalization and their interconnectedness (Photos: Softec)The objective has a significant influence on the introduction of new digitalization measures. These should be as specific as possible in order to tailor the measures and select suitable solutions.
Suitable objectives could be, for example
- Time is to be saved in incoming goods.
- Plant utilization in production should be improved.
- Power peaks in production should be avoided as far as possible.
A concrete objective also makes it possible to check afterwards whether the set goal has been achieved [1,2]. By analyzing the return on investment (ROI), the costs and benefits of a measure can be compared and a period of time can be defined from which the benefits outweigh the costs. This approach entails some complexity, especially when it comes to topics such as digitalization. Many aspects are difficult to quantify or the achievable effects can only be estimated with considerable imprecision [3]. A detailed consideration of the ROI of digitalization in relation to electroplating was discussed in the Surface Technology Yearbook Volume 74 "Costs/Benefits of Digitalization".
Sufficient tests or pilot projects are a helpful tool for the introduction of new technologies. This allows new ideas to be tried out on a smaller scale - with less effort - in order to better evaluate their efficiency and benefits in day-to-day work and to gather feedback from employees. For example, different technologies can also be tested and results compared.
The described order run serves as a tool for orientation in order to describe the potential benefits of digitalization measures and to demonstrate the technologies and solutions used in a practical manner.
Digitized order flow
An order for galvanizing thread forming screws serves as an example order. In the course of the article, we follow this order through the production process:
Incoming order
The first aspect of digitalization comes into play as soon as our order is received. Instead of the delivery documents arriving at the yard with the goods, they are sent in advance via electronic data interchange (EDI).
This means that all order information, such as quantity, the desired coating process, etc., is already available to submit a quotation. This quotation can also be created automatically on the basis of this information.
Once the quotation has been confirmed, order creation is also completed in no time at all, as the transmitted EDI information is used to generate the order. At the same time, the customer usually receives an order confirmation with a planned delivery date.
The transmission of order information via EDI not only speeds up the exchange between the customer and the contract finisher, but also improves the ability to plan, enabling better adherence to deadlines given the already short planning horizons and providing information as soon as the order is confirmed.
Even before the order is delivered, important steps have been completed digitally: the customer has been informed that their order is being processed and the order has been generated internally in the ERP system with all relevant information and is already scheduled in the system. In the next step, we will look at how our order is planned.
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EDI
EDI is a collective term that includes various protocols and formats that can be used to transmit data electronically. Various standards have been established which, for example, also reflect industry specifications. One example that is relevant for many contract processors is the VDA message formats for the automotive industry. In order to use EDI, a corresponding interface to the customer must be configured that enables the direct exchange of data between the two systems on the basis of such a standard [4].
Planning
The customer also sent us a desired delivery date for our order. Based on this date, our order is transferred to planning together with other open orders. In addition to new orders, feedback from production, for example with last-minute rescheduling, also influences the planning of future orders.
Every order comes with restrictions such as the delivery date. In addition, there are the specifications of the processes used, pre- and post-treatments, maximum idle times and much more.
Our screws, for example, are barreled goods and have to be divided into several barrels for coating at one of the two zinc-nickel plants.
The more restrictions there are, the more confusing it becomes for the planners. Added to this is the flood of new information, changes and customer requests.
In the context of digitalization, automation can provide support with so-called "constraint programming". This involves mapping all constraints so that the planning tool can take all restrictions into account at all times. This allows the tool to calculate how planning can best be optimized for the current order situation based on all constraints [5, 6]. Constraint programming is possible in combination with machine learning, a tool from the field of artificial intelligence. Using existing data sets, the AI is trained to recognize patterns and special features that easily escape the human eye - in order to further increase optimization [7].
Our order is scheduled automatically. If the delivery of our screws is delayed, the tool reschedules so that the order can still go straight into production as soon as the goods have been unloaded.
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Variant production
There are complex requirements in the day-to-day work of electroplating companies. There are items that also need to be produced in different variants, i.e. with different geometries, process steps, etc. Normally, these articles all have to be created individually with article numbers and their master data. Variant production avoids this step by allowing the data to be adapted at order level. This information can also be transmitted via EDI - like article master data. This offers the advantage that the ERP system can calculate directly with the changed values, which can result in different prices and different production times. These are thus taken into account from the outset and can, among other things, enable a smoother planning and production process.
Delivery of the goods
As soon as the screws are unloaded in several KLTs, preparation for production no longer takes much time. The order and the operating order have already been created. To ensure that the goods can be tracked seamlessly through production, a folder with an RFID transponder is attached to the outside of the containers in this step. RFID antennas are placed at the gate between incoming goods and production, which read this transponder as soon as the forklift truck with our screws enters production. The system is informed that the goods have been transported and are now in production. This traceability is not only particularly helpful internally in order to know the location and condition of goods, but is also particularly interesting for feedback to customers who, for example, enquire about the status of their order by telephone.
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RFID in electroplating
Radio-frequency identification, or RFID, is a technology used in retail, for example, to track objects such as items of clothing. The use of RFID requires transponders that are attached to the moving objects, antennas at key points in the plant where the movement of the objects is to be reported, and readers at the antennas that process the signals received.
A limiting factor in electroplating was the metal-heavy environment, which negatively affects the functionality of radio waves. The described folder avoids this problem by attaching the transponders to the outside of the container at a sufficient distance from the metal, which enables good readability even with metal goods and containers such as mesh boxes.
Production
Delivery bill of a sample order with details of the coatingWefollow our order into production. On the way to the plant, the forklift truck drives past a large monitor on which the current orders are displayed. This is linked to the planning and updates automatically so that changes are immediately visible and all employees are informed of them. The view switches through the individual systems and here we also discover our order again, which is scheduled for the zinc-nickel system. With this information in view, the forklift truck heads purposefully for the right system and the coating of our screws can begin.
While the movement of goods is monitored with RFID, the processing of the individual work steps is reported back directly to the systems via the production data acquisition (PDA). To do this, employees use an industrial smartphone, scan the corresponding barcode on the work order and can use an app to transmit start and completion notifications for the individual work steps. This information is also reflected on the large monitor, which shows the progress of individual orders with bars. If more precise information is required, the order monitor can be called up on a tablet, for example, to display the details of our order. In this way, the screws run through production step by step.
Meanwhile, an employee looks at the system through their smartphone camera and sees the system's key figures on a virtual board: electrolyte concentration, current, temperature curve, etc. All values are displayed in green, everything is fine.
This brief check serves to ensure that all production parameters are correct in order to guarantee consistently high product quality.
An augmented reality (AR) app is running on the smartphone for this purpose. This displays information in the camera image where it is relevant. One advantage for employees is that they can easily carry out the inspection directly at the system. It is not necessary to walk to a terminal or an office to check the values. If there are any deviations, the adjustment can be made directly on site and then verified by taking another look through the cell phone.
Display of the order on an order monitor with the current processing statusOurorder passes through several stations in production until the final completion notification has been issued. The finished coated screws are checked before they are sent to the outgoing goods department.
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Augmented reality
...is a versatile tool that is used in this context as a smartphone app. The app uses the camera and the smartphone's internal sensors to capture the surroundings and link them to previously placed data panels. These panels are anchored in a virtual model of the environment so that they remain spatially in place - like a picture hanging on the wall [11].
Quality assurance
For the inspection, the corresponding inspection protocol is stored with the item in the ERP system. A random sample of five screws is considered for our inspection. An employee reports back the test results via smartphone. He loads the test report via a barcode scan and is guided through the individual work steps by the app. Some inspection steps are carried out visually and a coating thickness measurement is also performed. All parts are reported as OK, the results are digitally logged in the ERP and our screws are sent on to the outgoing goods department for packaging and delivery.
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What can AI do in surface technology?
Artificial intelligence has been a key topic since the release of ChatGPT and DeepSeek. From entertainment to industry, a wide range of possible applications are being discussed - including in surface technology. A distinction must be made between language and machine learning models.
Language models generate dynamic, text-based answers based on large amounts of data, answer questions or create programming codes. However, they cannot control machines, but only describe their operation [8,9]. In surface technology, they could automate customer communication [10], send order confirmations and status messages and recognize missing information in requests in order to shorten processing times.
Machine learning models analyse large amounts of data, recognize patterns and optimize processes. They could evaluate production data in order to identify anomalies or quality problems - for example, due to interactions between successive items, such as hat nuts that are subject to heavy wear. This could be used to derive adapted production plans and measures for bath maintenance.
As the database grows, machine learning models improve through continuous training, make more precise predictions and identify potential problems at an early stage. This increases efficiency, quality and production reliability in surface technology in the long term.
If company data is also to be processed when using AI, compatibility with data protection plays an important role. Tools such as ChatGPT or DeepSeek run on servers in the USA or China, which is why the transmission of customer data or company secrets must be viewed extremely critically.
Instead, the current trend is to use AI models that run locally on computers in the company and are only active in the company's internal network. These have a certain "basic knowledge" with which they have been trained, which can be expanded using other internal company sources, such as knowledge databases.
Such a model - which is not connected to the Internet and third-party servers - can therefore access company and industry knowledge even more accurately, while at the same time ensuring data protection.
Outgoing goods
App for feedback of PDA data, with which the order status is updatedThe screws are brought to the outgoing goods area, the forklift passes the RFID antennas and the new location is automatically reported. In the outgoing goods area, the screws are packed in the small load carriers (SLCs) and prepared for dispatch. The folder with the RFID transponder is removed for reuse.
Loading begins as soon as the truck pulls up. The individual containers are scanned using an app to automatically create the loading list. A delivery bill is not required at this point; this is sent via EDI.
In addition to the loading list, the employees document the load securing for the customer using a photo. This is also attached to the order as an additional document via barcode scan and app and is immediately available in the ERP system.
The order then leaves the yard and is on its way to the customer. The delivery bill reaches the customer via EDI even before the goods arrive and transmits all order information. The invoice is also sent via EDI.
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Apps
Smartphone apps are practical to use on site in a wide variety of departments to record information directly as part of a work step. The focus of the apps on the respective task enables a simple user interface for uncomplicated operation. In addition, employees are familiar with using smartphones from their day-to-day work, which further reduces the barrier to use. The information is linked to the ERP via barcode scans so that it ends up in the right place.
Outlook
A digitized order flow was illustrated using an order as an example, and various aspects of digitization were considered and contextualized. In the end, the central question for contract finishers always remains: What are the benefits of digitalization?
The examples have shown that this question can have very different answers. A fully digitized order process ensures that media disruptions are avoided, i.e. there is no back and forth between digital data and paper. Information is transmitted directly and largely automatically. This reduces the possibility of transmission errors and ensures more efficient interaction within the company and in the supply chain.
Looking at individual solutions, there are very different advantages: For example, sending order confirmations or invoices via EDI not only saves time, but also simply postage costs. The detailed tracking of goods with RFID can increase customer satisfaction by keeping customers directly informed about the status of their goods.
The implementation of solutions often reveals unexpected synergies, especially through the interaction of several technologies. The question: "What are the benefits of digitalization?" cannot be answered conclusively in advance, many aspects are difficult to quantify and there is still a lack of reference companies that comprehensively demonstrate the effects.
Digitalization is and remains a key issue for surface technology that every company must address. It is important to examine individually which approaches are suitable for digitizing your own company. It is often enough to start at a single point that offers optimization potential. Once the first step in digitization has been taken, ideas for further aspects usually emerge, which can be networked and digitized in subsequent steps and thus generate added value.
Literature
[1] Beck, M., Plekhanov, D., Wörter, M. (2020) : Analysis of digitization in the Swiss economy, KOF Studies, No. 153, ETH Zurich, KOF Swiss Economic Institute, Zurich.
[2] Mengen, A., Dietrich, L. (2020) : Digitization and economic efficiency. Economic efficiency analysis of digital B2B solutions for companies, Wissenschaftliche Schriften des Fachbereichs Wirtschaftswissenschaften, No. 31-2020, Hochschule Koblenz - University of Applied Sciences, Department of Economics, Koblenz.
[3] Schlotmann, R. (2018): Digitalization for SMEs: The "Digital Impact Management" method, Springer Vieweg, Frankfurt.
[4] Neuburger, R. (1994): Electronic Data Interchange: Possible applications and economic effects, Gabler Verlag, Wiesbaden, pp. 4-5.
[5] Apt, K. (2003): Principles of Constraint Programming, Cambrigde University Press, Cambridge, pp. 1-5.
[6] Rossi, F., van Beek, P., Walsh, T. (2008): Chapter 4 Constraint Programming, Foundations of Artificial Intelligence, Elsevier, Volume 3, pp. 181-211.
[7] Bertolini, M., Mezzogori, D., Neroni, M., Zammori, F. (2021): Machine Learning for industrial applications: A comprehensive literature review, Expert Systems with Applications, Volume 175, 2021, 114820.
[8] Mohammed Waseem Ashfaque, M. W. Sr. (2022): Analysis of Different Trends in Chatbot Designing and Development: A Review, ECS Transactions, Vol 107, 7215.
[9] Lourdusamy, R., Gnanaprakasam, J. (2023): Expert Systems in AI, Components, Applications, and Characteristics Focusing on Chatbot. In: Data Science with Semantic Technologies, CRC Press, Boca Raton.
[10] Andrade, I.M.D. and Tumelero, C. (2022): Increasing customer service efficiency through artificial intelligence chatbot, Revista de Gestão, Vol. 29 No. 3, pp. 238-251.
[11] Hellmuth, M., Windhab, A. (2022): Making hidden information visible. In: Yearbook Surface Technology Volume 78, Sörgel, T. (ed.), Eugen G. Leuze Verlag, Bad Saulgau.
