In the field of industrial automation, many engineers—including myself—often wonder: How should a control optimization project truly be executed? After years of hands-on experience, countless project iterations, and learning from industry veterans, I have developed a clearer understanding of the guiding principles. While this is not a definitive methodology, these insights have significantly improved both project efficiency and outcomes.
Here, I summarize five fundamental principles that form the backbone of successful control optimization projects:
1. Divide and Conquer
The primary goals of most customers when initiating a control optimization project are safety and economic efficiency. However, since many of these improvements are already in place, the remaining issues are often hidden, unrecognized, or too costly for the customer to address independently.
Unless you’re an expert in a specific industrial process—be it petrochemical, fertilizer, metallurgy, or building materials—it’s challenging to directly optimize for safety and efficiency without a clear focus. Therefore, a practical approach is to start with operator actions and alarm analysis.
By analyzing frequent operations and alarm events, we can identify operational pain points. These pain points serve as leverage points, breaking down high-level goals into smaller, actionable targets. This method simplifies complexity and fosters a shared understanding between you and the client.
2. Simplify Complexity
There is no perfect solution—but there is always an optimal solution for a given context. Every problem can have at least three feasible solutions, and the focus should be on solving problems efficiently rather than showcasing technical complexity.
Avoid the “hammer syndrome” where every problem looks like a nail. Instead, remember the ultimate goal: “The purpose of sharpening a blade is to cut wood, not to admire the blade.”
A good control solution should be:
Simple, stable, efficient, and cost-effective
Understandable to operators and maintainers
Aligned with the customer’s capabilities, budget, time constraints, and preferences
Strive for standards and clarity, not overly clever tricks. Simple does not always mean correct, but complex almost always indicates the wrong direction.
3. Leverage Collective Wisdom
Even if you’re a process control expert, you’re not likely to be an electrical engineer, compressor specialist, and chemical process expert all in one. That’s why building a cross-functional project team is critical.
For example:
A roasting furnace control issue may require instrumentation adjustments
Frequency ramping in a VFD could be programmed in the DCS or directly configured in the VFD
Involve experts from electrical, instrumentation, mechanical, operations, and process teams. They offer unique perspectives that contribute to holistic and sustainable solutions. Trying to solve everything alone is neither efficient nor feasible.
4. Be Realistic and Objective
Each control optimization project comes with constraints—be it time, resources, technical limitations, or organizational habits.
Being realistic means:
Acknowledging that you can’t solve everything, but you can solve many things
Understanding the root causes of problems and identifying the real constraints
Listening to stakeholders but also having independent judgment
Unresolved problems usually point to gaps in knowledge or capability. Once a problem is clearly defined, solving it becomes much easier. Don’t be overly attached to assumptions; adapt your solutions to changing circumstances.
Also, stay open to learning through operations: every pain point in manual operation hints at an automation opportunity. Trust that every manual process can eventually be translated into a simple and optimized solution, even if current conditions are not yet ideal.
5. Embrace Continuous Improvement
Don’t aim to solve everything in one go. Industrial systems are dynamic—what works today may need adjustment tomorrow.
Instead:
Prioritize low-hanging fruit to win trust and recognition
Apply the 80/20 rule: solve the major issues first
Use a step-by-step improvement approach
Even if you find the best solution today, changing conditions may require updates. What once seemed impossible may become easily achievable with future capability upgrades.
Each stage should aim for realistic short-term goals, while also planning for long-term evolution and refinement.
Conclusion
Control optimization is not about applying complex algorithms or showcasing technical prowess. It’s about finding practical, efficient, and scalable solutions that align with customer needs and project realities.
These five principles—Divide and Conquer, Simplify Complexity, Leverage Collective Wisdom, Be Realistic, and Embrace Continuous Improvement—serve as a proven roadmap for navigating complex industrial environments and driving lasting value through automation.