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Dipesh Patel is the President & CEO of DP Gayatri, partnering with OEMs and Contract Manufacturers to automate and scale operations. A seasoned management consultant and graduate of the UofM Carlson School of Management, he brings strategic leadership to a portfolio of manufacturing and automation companies delivering factory automation, contract assembly, facility relocation and expansion, and supply chain localization across the U.S. and Latin America.
A factory automation strategy that starts with "here is the technology we are going to deploy" is not a strategy. It is a procurement plan. The technology question is the last question in a real automation strategy, not the first.
The real strategy starts with: which constraints in our operation are the binding constraints, and which of those would respond to automation? Most plants automate around the wrong constraint and end up with a faster bottleneck somewhere else.
Walk the floor. Track WIP at every station. Time the actual cycle, not the engineered cycle. The constraint is the station where WIP queues, where overtime happens, where the supervisors spend their time. It is almost never the station that the plant manager assumes.
Not every constraint responds to automation. A constraint driven by quality variation may need process engineering before it needs a robot. A constraint driven by changeover time may need SMED before it needs a cell. A constraint driven by demand volatility may need scheduling before it needs hardware.
Automation responds well when the constraint is repetitive, cycle-time-bound, and the inputs are consistent. It responds poorly when the constraint is variability, judgment, or exception handling.
If the constraint is throughput and automation can unlock 30 percent more capacity, the upside is the revenue or margin associated with that additional throughput. If the constraint is labor and automation can reduce 1.5 FTE per shift, the upside is the labor cost net of capital and ongoing operating cost.
Quantify before you start specifying equipment. Most automation projects justify themselves on labor displacement when the real value is throughput unlock or quality improvement. Different value lever, different equipment choice.
If the value is throughput, optimize for cycle time. If the value is labor displacement, optimize for cost. If the value is quality, optimize for capability and repeatability. Each value lever points to a different set of equipment choices, integrators, and operating models.
The automation that works is the automation your team can run. Plan operator skill, maintenance discipline, spare parts strategy, and troubleshooting protocols before the cell ships. The percentage of cells that underperform because the operating model was not built around them is high.
Single cell, single constraint, clear before-and-after metric. 12 to 30 month payback. Easy to justify, easy to execute, easy to maintain. Most automation should look like this.
Multiple cells with common platforms, deployed as demand grows. Higher capital efficiency than building all-at-once. Requires platform discipline and integrator continuity.
New product or new line, automation designed into the process from day one. Higher risk but higher reward. Requires deep operator-engineer collaboration.
"Let us automate the factory" as a general initiative, with budget and a deadline but no constraint analysis. The result is usually a portfolio of half-finished projects that consume capital and management attention without producing the throughput or labor outcomes that were promised.
Start with constraint analysis. Test for automation responsiveness. Quantify the upside. Match the technology to the value lever. Build the operating model before the cell arrives.
DP Gayatri runs that framework for OEMs and manufacturers across the upper Midwest and Mexico. Our consulting practice exists to keep automation strategies honest before capital gets committed. If you are early in an automation plan and want a second view before the equipment selection happens, that is the conversation we want to have.
