Short Answer
Most industrial machinery selection errors start with a model or price before defining the part, output and quality; rely on one catalogue figure; or ignore trials, auxiliaries, support and total cost.
Mistake 1: Starting with price or model
Price matters, but it does not prove fit. Start with the part, process and demand, then request a configuration that serves them.
Mistake 2: An incomplete application file
Define drawings, dimensions, materials, thicknesses, tolerances and batch size. The finished part determines the process, axes, workholding, automation and tooling.
Mistake 3: Relying on one headline figure
Record current and target output per shift, cycle time, rejection, setup time and operating hours. These figures reveal whether a proposal removes the real production bottleneck.
Mistake 4: Ignoring auxiliaries and full process
Add freight, installation, training, tooling, software, energy, maintenance, spares, downtime and financing to the purchase price. A higher-priced machine can be less expensive over its working life.
Mistake 5: Skipping an acceptance trial
Run a test on representative material and parts. Document supply scope, exclusions, warranty, acceptance criteria, training and post-delivery service.
Mistake 6: Ignoring downtime and support
Purchase price does not show failure, response, spares and training impact. Include them in risk and total-cost evaluation.
Mistake 7: No owner or measurement
Assign an implementation owner and post-startup measures such as good output, quality, downtime and cost. Otherwise success cannot be proven.
Frequently Asked Questions
What is the highest-risk mistake?
Buying before the application and acceptance criteria are defined.
Is brand name enough?
No. Evaluate the actual configuration, local support and application result.
How is bias reduced?
Use one scoring matrix, a documented trial and a cross-functional team.
Next Step
Share your part, material, target output and site requirements with SAKKARY MACHINERY for a technical review of industrial machinery.
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