I manage equipment and service procurement for a 280-person mineral processing company. Over the past six years I have audited roughly $12 million in crushing, grinding, and screening purchases. I have also spent enough late nights reconciling actual costs against approved capital to know what gets missed in quote comparisons.
Use this checklist when two things are true. First, you are comparing large equipment packages or process solutions, not just buying a replacement belt. Second, the decision will affect operations for more than five years. I first built the checklist in 2021 after a mill project taught me not to compare supplier brochures. It has grown with every project since.
If you are lining up FLSmidth and ThyssenKrupp mining proposals, this list will make the differences visible fast. It will not tell you which vendor to pick. It will tell you what to ask before somebody inflates the “real” cost later.
Every plant I have worked with is hungry for something: more throughput, lower energy per tonne, fewer liner changes, more predictable maintenance. That hunger needs to be stated as a measurable condition, not a product preference.
A weak brief sounds like: “We need a bigger mill.” A useful brief sounds like: “We need to increase SAG mill feed from 3,400 to 3,900 t/d at 8% moisture, while maintaining a P80 of 180 microns.” When hunger is that specific, vendors can point at trade-offs, not just quoted advantages.
The first time I compared two crusher quotes, I thought the price difference was 18%. After I listed exactly what each quote included—foundation bolts, starter panels, chutes, commissioning hours—the gap dropped below 4%. The scope boundary is the cost controller’s best friend.
If a proposal says “standard scope,” ask what is standard. Does it include the lubrication system? Gearbox? Vibration monitoring? Operator training? I have seen all of these appear as change orders after signing.
Use the same baseline for both bidders. That seems obvious, but it is the most common omission I see in capital requests.
Equipment price is a visible number. Energy consumption, wear parts, and unplanned downtime are less visible but often larger. In one review of a grinding circuit, I found that wear parts and service represented 2.3 times the purchase price over its first six years. That does not mean the machine was bad; it means the business case could not ignore consumables.
Build a model with five main lines: installed cost, energy, maintenance and wear parts, downtime, and residual value. Use site data, not supplier averages.
“Global network” sounds strong until your plant is down and the nearest needed bearing is an international air freight shipment away.
During an audit in 2023, I asked two suppliers to specify the closest warehouse location for their top 20 critical spares. One supplier gave city, stock level, and lead time. The other said they had “global locations.” That distinction told me more than any presentation.
Add this to the RFP: required stock level and response time. If suppliers cannot commit to a response time in writing, it is not a service guarantee; it is a hope.
At a previous site, we bought from a supplier with a regional office listed on their website. When we needed a field service engineer, the nearest available person was nine hours away. The office existed; the service depth did not.
Ask who will actually help after commissioning. Get the name, role, and approximate location of the service engineer and process engineer assigned to your account. For larger programs, ask about remote monitoring and escalation. A vendor with multiple engineering centers is more likely to have this capacity.
I used to treat site visits as a chance to shake hands. Now I use them to test whether a supplier can solve process problems, not just sell equipment.
A good example was my visit to the FLSmidth Chennai campus in 2024. I went expecting a standard engineering office. The conversation quickly shifted from product specifications to process data, testing, and where engineering support sat after handover. That is not enough by itself to choose one vendor, but it tells you whether you are buying from people who understand the process or from people who are reselling a catalogue.
The final step: availability and throughput have to mean the same thing to both sides. In my experience, disputes are rarely about the guarantee amount; they are about whether the guarantee applies.
Use standard definitions. For example, ISO 14224 gives a common basis for classifying equipment failure and operating data. If your contract refers to availability, define what constitutes an operating hour, scheduled stop, forced stop, and standby hour. If you do not define them, the financial close-out is where misunderstanding shows up.
I also prefer a demonstration period. The machine should achieve the guarantee under monitored operating conditions for 30 to 90 days before final acceptance is signed.
No checklist can prevent every bad decision, but these are the four that show up the most in my own files:
What changed in the last five years: data. Machines now report on themselves, and automated monitoring can often tell you about a bearing issue before the maintenance crew hears it. That has moved the comparison from mechanical specifications to data infrastructure.
What hasn’t changed: fundamentals. Bearings still need lubrication. Alignment still matters. Operators still need training. The best procurement decision is one that keeps those fundamentals from being lost under a clever capex model.
I have made enough expensive mistakes to stay humble. This checklist does not make the decision easy; it makes the comparison visible. When the project kicks off, you will know which numbers were assumed and which were actually priced.
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