22 June 2020
Excellent product data is a determining factor during the engineering process. There are many problems that the engineer encounters daily when the product data is not properly managed.
For this blog, we had an interview with Marcel Schapendonk of Hoppenbrouwers Techniek in Udenhout. Marcel is a lead engineer and has a coordinating role in projects within the Industrial Automation department. He also supervises the optimization of the (hardware) engineering process from quotation to delivery. Within his position as a lead engineer, he actively contributes to the development of the BeeFinity platform. Marcel, thanks again for your time!
“To select the right components based on specifications during the design process, it is important that these specifications are clear and complete. From a commercial point of view, it is also useful to select components for which good price agreements have been made. Engineers who have been “coming along” for some time often know a lot by heart. But especially when the organization is still growing, this information should be accurate and fully available to everyone who needs it.”
What do you think of manufacturers whose product data is not correct or not fully available?
“You try to avoid these manufacturers. Unfortunately, that is not always possible. As such, it takes so much energy and time to collect the correct product data, which is why you eventually will use products from other manufacturers. As a consequence, the quality of the design decreases, which is something that we absolutely want to avoid. Sometimes you do look up the missing information, but that depends on how often you will use the products in other projects and how important that part is for your system.”
“At our engineering department, the products are currently still managed in Eplan P8. In Eplan, the products with their relevant spec’s must be recorded to create the design. We work together with approximately 20 engineers who are all able to create and adjust their own required products. To ensure that uniformity is created, we have drawn up a manual in the past. The manual, for instance, contains information about which specification fields must at least be entered. Despite this manual, each engineer has his own working method, which still creates variation sometimes.”
When is the product data quality sufficient or good enough?
‘Difficult question. What we think is good today may not be good enough next week or next year. There may be new developments that make you demand for other available information. We have already asked ourselves this question, which made us determine that we want to have specific fields already filled in. For now, that means 100% quality, but this may be different next year, and we might therefore need new data. As such, the 100% of today is the 85% of tomorrow and hence is growing. 10 years ago the (important) product data may have consisted of 10 data fields, yet, this is now at least the double. In the past, a good estimation made by the engineer was sufficient, nowadays you want to check the estimation with a calculation based on data. Because the data is now available and automated, additional product data is certainly relevant.”
What is the influence of the growth of your organization in the field of product data management?
“If you can make clear agreements with a small team of people and you get used to each other quickly, there is less need to strictly capture everything. Yet, because the organization is growing rapidly, all information must now be available to everyone, at all times. The engineers who have been there for a long time have a great deal of information stored in their brains, however, this does not work efficiently. Namely, someone who is new to the organization does not know the type numbers of our frequently used products by heart. In a situation like this, it would be very convenient when this employee can select products based on characteristics. So if this is well structured, it will be much easier to find the right product. And that’s what you are aiming for. When the need to properly record all data is growing in your organization, you must realize that it should all be done in the same way.”
What are the main problems your organization is facing?
“Product data management is maintained in different systems and by different stakeholders. For example, a work planner uses this information in the ERP system, whereas an engineer uses it in CAD software like Eplan P8. As a result, there are sometimes ‘mismatches’ between the information that the engineer uses during the design and the information that is required when ordering. To illustrate, if the EAN/GTIN number is unknown, it depends on the clarity of the product description whether the correct product is ordered. A description is usually not unique, so it may be possible that there are multiple options with the same description. So how do you make sure which product is the right one? If a clear Product ID/EAN number is known, you immediately have the right match. Often, that number is missing and therefore the decision depends on the knowledge of the person who converts the engineer’s parts list into the purchase order. This regularly goes wrong. Adjusting this error is time-intensive and costs money in your process and leads to frustrations as well.”
‘As an engineer, you can also often not easily see what the lead time of a product is and whether it is in stock. Nowadays, hardly any stock is kept in the workplace, so to be able to switch quickly, you would want to know during the design process whether the item can be delivered quickly or not.’
Do you have an ambition in the field of product data management?
‘The ambition that I have is that all data is immediately available and fitted in one clear standard, so every manufacturer fills it out in the same way. The ETIM standard is already there, but this is not enough. The ETIM standard should be combined with CAD data and related standards.”
And how do you deal with this as an engineer/work planner/purchaser? Together with our appreciated clients, we’re looking at possibilities to tackle and optimize these diverse challenges in the field of product data management. With Hoppenbrouwers as a proud example and partner from the very beginning, we have collaborated intensively in recent years to learn from each other and work out a win-win solution together.
22 June 2020
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