The calculations lived in a few people's heads. Now they are a product.
Turning engineering know-how into an in-house product: over 5,500 catalogue references, automatic drawings and a pricing tool that goes from parts list to quotation.
The challenge
Pihasa manufactures the supports that hold up the piping in an industrial plant. Deciding which support goes at each point is not picking from a catalogue: you have to calculate loads, movements, temperatures, travel reserve and allowable variability, and check that the parts of the assembly are compatible with each other.
The company had the people who knew how to do it. The problem was that that knowledge was written down nowhere: it lived in the experience of the engineering and design team. Every calculation depended on who did it, and a full installation runs to between one hundred and one thousand supports.
That meant three things at once: dependence on very few people, long lead times at the quoting stage, and results that could vary from one project to the next. And no way to grow without hiring more engineers with that same experience.
Approach
We started with the diagnostic: walking the whole process, from the specification arriving from the customer to the drawing and the quotation going back out. The aim was not to automate what was already being done, but to understand which decisions were being taken and on what criteria.
The decisive step was making the tacit explicit. The criteria the team applied from experience became compatibility and validation rules: which combinations of parts are valid, which model matches each load and movement range, what the system flags when something does not fit.
Pihasa Assistant was built on those rules, an in-house product covering the seven support types — variable, constant, rigid and dynamic — with the full house catalogue embedded in the calculation itself. Then came a pricing tool that takes the parts list and returns a quotation based on the specification received.
The company then took an unusual commercial decision: giving the software away to its customers. The know-how stopped being an internal cost and became the way to be present at the customer's design table.
- A walkthrough of the whole process, from customer specification to drawing and quotation
- Engineering criteria turned into explicit compatibility and validation rules
- A catalogue of more than 5,500 references embedded in the calculation itself
- Seven support types covered: variable, constant, rigid and dynamic
- Automatic generation of 2D and 3D drawings and bills of materials
- Excel import and export, with data validation on the way back in
- Revision control support by support, so you can return to an earlier version
- Export to AutoCAD formats, images, Office and PDF
- A pricing tool that turns the parts list, in-house or the customer's, into a quotation
- A public knowledge base with the product documentation
Key outcomes
60%
less time to calculate and quote a complete installation of between one hundred and one thousand supports, with calculations and drawings automated.
5,500+
catalogue references embedded, each with its optimal calculation and its compatibility rules attached.
€0
for the end customer: the software is given away, and the company's know-how went from internal cost to commercial argument.
13
years of continuous work, from digitalising the calculation in 2013 to the AI automation under way now.
What used to be an engineering job repeated support by support is now a datasheet you fill in once, out of which come the valid model, the 2D and 3D drawing and the bill of materials. Right now we are working on the next layer: using artificial intelligence to automate the commercial processes and document management that surround the calculation, which is where the time the software has not yet touched is concentrated.
Turning know-how into a service
The interesting part of this case is not technical, it is commercial. A manufacturer of metal parts decided to take what it did best — calculating — and give it away as software. The result is that its customers design with its catalogue in front of them, in its tool, under its rules. Digitalising the know-how did not only make the work faster inside: it changed where the company sits in relation to its customers.
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