Break the Rules: A Hybrid Approach for Tuning Very Slow Processes
Practitioners of every age know that tuning very slow processes presents a challenge when faced with rigid time constraints. Specifically the time needed to perform the requisite bump
tests isn’t always practical. In order to tune such loops quickly some practitioners have
successfully applied a hybrid approach. While this approach won’t be found in university
textbooks, it has been proven to do the trick in a range of situations. Skeptical? Read on.
Cascade Control: Improving Disturbance Rejection Through Advanced PID Control
There’s a common misconception in various corners of the process industries related to advanced
process control (APC). When the topic of APC is raised it’s not uncommon for practitioners to
immediately think of complex fuzzy logic and model predictive solutions. But a broader view of APC also includes advanced applications of the Proportional Integral Derivative (PID) controller. Chief among those APC solutions both used in industry and based on the PID is Cascade Control.
Setting the Standard: Top 3 Considerations When Tuning PID Controllers
When the PID controller was first introduced manual tuning was the only game in town. As tuning
software entered the market it consistently failed to address common challenges associated with industrial control. Those lapses provided the rational for a generation of practitioners to continue tuning PID loops by manual methods. Recent innovations now make software the clear and superior option. But benefitting from tuning software requires practitioners to move beyond those historical misconceptions.
Avoiding the Traps: A Plan for Successfully Evaluating New Manufacturing Technologies
Innovation can be a manufacturer’s worst nightmare especially when it comes to conducting formal evaluations. From conflicting priorities and disagreements over schedules to ineffective communications and a lack of engagement from key constituencies, any number of project elements can go wrong. To make matters worse the rate of innovation is increasing. It is
creating a gap between technology and the labor its intended to help. In spite of this trend simple
steps can be taken to assure that evaluations are fully aligned with a manufacturer’s goals and
existing resources. There is a way to avoid the traps.
Top Secret: How Regulatory Control Evaluations Uncover Hidden Opportunities for Production Gain
While most technology investments require proof before a purchase can be made, each
production facility has unique attributes for which general industry-wide benefits don’t necessarily apply. A short-term, highly focused evaluation can equip manufacturers with clear financial evidence. Equally important, an evaluation illuminates how the associated KPIs both align with the facility’s annual production goals and allow management to remain on top of progress.
Hijacked: Three Questions to Determine if Your Tuning Software is Ready for the Real-World
Practitioners look to tuning software to steady their control loops and improve performance. In particular they count on software to tackle complex, oscillatory conditions. But some software vendors have hijacked terminology that describes recent innovations in dynamic process
modeling. All the while they still require users to steady the loop before their products will work.
That is, all but one.
CLPM RFP Checklist: Considerations for Your Control Loop Performance Monitoring Solution
There is a growing number of CLPM solutions on the market that offer a range of capabilities.
Understanding which product suits your unique monitoring and diagnostic needs can present
challenges. As with other automation technologies there are numerous aspects of CLPM that should be considered prior to writing your request for proposal and making an investment. This
article offers basic guidelines for evaluating and selecting an appropriate CLPM solution.
Why the Model Matters: Accurate Modeling is the Key to Improving Production Throughput
When a control loop can be maintained at a steady-state before performing a step test, it is
relatively easy to tune manually. It’s when process conditions are complex that practitioners
need the help of software. Historically that’s when software has failed — and failed consistently. But something has changed in the modeling of ‘real world’ processes