Learn three ways process optimization helps businesses thrive in challenging times and how you can lower costs and improve the efficiency of your organization.
What is Business Process Optimization, and How Does it Work?
Business process optimization is a powerful method for company improvement through automatic simulation optimization. It involves identifying and analyzing business processes, recognizing areas for improvement, and implementing changes to streamline the process and eliminate waste. However, optimization doesn’t stop with improvement – it seeks to optimize to the point where process resonance occurs.
Resonance is a phenomenon where the system begins to vibrate with larger amplitudes at the resonant frequency. Resonance can occur in various types of systems, such as mechanical, electrical, and acoustical systems. For example, the swing oscillates if you push a child on the swing. If you move the swing at the right frequency, it will start to swing with larger and larger amplitudes. The increase is because the push frequency matches the swing’s natural frequency, and resonance occurs.
Process resonance is when all system elements synchronize to produce the highest output with the least effort. Unfortunately, process resonance is brutal to find when experimenting manually – many systems have more than 10,000 possible solutions.
With optimization, the computer experiments autonomously to find situations where process resonance occurs. These experiments happen rapidly, and the computer knows when experiments aren’t viable, immediately eliminating thousands of potential candidates. Conversely, options that show promise become a springboard for further experimentation. It’s kind of like the selection process for the Titisee fly. The weak ones die off, and the strong ones continue to thrive.
The evolution of hunting for the best solution often leads to process resonance – that little extra is pure profit or that nudge that makes good companies great.
Let ProcessModel work while you sleep
The modern computer can process a gazillion calculations per second, yet we only use a fraction of its power. The computer stops with us when we go home, stop for lunch, or even switch to work on another project. But with ProcessModel, once you set a target for the optimization, it keeps searching even when you decide to take a break. You could go home for the night or out on a date, and ProcessModel continues to hunt for process resonance – not requiring your input. So you get a good night’s rest and the answer in the morning.
Uncover solutions you don’t have time to try or might overlook
How many experiments do you have time to perform? How will you decide which to eliminate if you can’t run all the possibilities? Some people quip, “use a design of experiments.” That’s a great suggestion, but it doesn’t work for the problems encountered with simulation. Design of Experiments is practical when you can set binary variables such as Hot or Cold, not what temperature we should use. Simulation adjustments often fall into the latter category, where the variable changes through various possibilities.
To calculate the number of possible solutions, you multiply the range of the first variable, the range of the second variable, the range of the third variable, etc. The variable is the range of motion for the parameter you want to adjust. For example, variable one might be the potential adjustment for the number of people in an area (such as 15 to 20). Adjustments could include any of the following:
- Number of people
- Pieces of equipment
- Type of equipment
- Process changes
- Routing changes
- Shift changes
One example of the range of changes in a moderate-sized process = 5 * 6 * 3 * 4 * 7 * 3 * 6 * 5 — which equates to 226,800 possible experiments. I don’t know about you, but I don’t have time to run a thousand experiments, let alone 226 times that amount.