Throughput Analyzer

The Activplant Throughput Analyzer provides a software solution to finding production constraints—a solution that has otherwise eluded manufacturers. Whether it be on production lines that produce complex assemblies, or on lines that run at high speed with relatively few manufacturing steps, the challenge has always been to find the equipment that constrains your manufacturing potential. You know you can get more from what you have, but you can't unlock the puzzle.

Throughput Analyzer requires minimal configuration to identify constraints, so it is typical for the discovery and implementation phases to take only two to three months, and for users to start seeing results only a few weeks after that. Most of our customers see an ROI within only a few months of service.

Applying proven theory

In developing the Throughput Analyzer, Activplant took the Theory of Constraints (The Goldratt Institute) as the model for understanding constraint analysis, and the tenets of the Toyota Production System (Lean Manufacturing) for an understanding of how best to present the analysis. Throughput Analyzer reporting starts with intuitive dashboards that present plant, area, and line level metrics for OEE, First Time Through, and Attainment. You can then drill-down to the asset level to find your constraints. All dashboards use a color-coding scheme to highlight performance, so users are directed to the areas in your production environment that require attention.

So what is so unique about Throughput Analyzer?

In short, it is the patented Throughput Capability Metric (TCM), a metric that unambiguously finds your constraints in a matter of just a few short weeks. And after you fix your current constraints, it continues to work to find the next constraint. With each fix, your production output increases, as with Throughput Analyzer, you are always directed to the asset that is hindering your output to the greatest extent.

How does Throughput Analyzer do it?

The TCM uses historical data to build statistical averages of the performance of every asset on your production lines, and highlights those that are constraining you from reaching your goals. You get plant, department, area, and line level understanding of OEE, Attainment, and First Time Through, and the TCM for each asset. You also get Top 10 Constraints reports (ranked by importance) and KPI Summary reports for each of the organizational levels in the plant, and you can view these from the perspectives of individual shifts and by week. At the asset level, you get detailed downtime reporting and reports that highlight your production losses by category.

How is this better than my current methods?

Many plant management professionals use OEE as their measure of efficiency and Downtime reporting as the basis of their continuous improvement projects. If this is how you work, Throughput Analyzer provides a much better answer to your needs.

OEE tells only half the story

Activplant Corporation contends that while OEE provides an excellent macro level understanding of efficiency at the plant, area, department, or line level, it is unable to provide the required focus at the asset level. The Theory of Constraints states that a line can run no faster that its slowest contributor. As a result, each asset that is able to run at a pace that is faster than this slowest is constrained to run at the speed of the slowest. This means that all assets, during a selected period contribute to the same quantity of quality units of production, so all assets exhibit approximately the same OEE metric as that for the line. OEE provides a tool to find the slowest line, not the slowest asset.

Fighting downtime limits your vision

Conventional thinking contends that if you concentrate on downtime issues, you must find your constraints as each piece of equipment must be running in order to produce. To support this thinking, downtime is relatively easy to measure when compared to any of the other categories of lost production, and so, understandably, plant managers concentrate on what they can measure.

The problems with focusing on downtime:

• Downtime reports do not recognize issues that rob you of output but do not show up on downtime reports, such as training issues that do not trigger a downtime fault
• Downtime reports do not recognize concurrent downtime issues, and when faults are concurrent, is there a causal relationship between them, such as downtime being caused by blocked or starved conditions
• Downtime reports do not recognize conditions where a downtime did not cause a slow-down in production, such as when an asset typically runs faster than the ideal to the extent that it keeps a downstream buffer from emptying, even when it goes down
• Downtime reporting can skew your understanding if the criteria used does not match your constraint finding needs, such as a Top 10 list by downtime duration that doesn't catch the asset that goes down very frequently, but only for very short periods
• Downtime reporting leads to reactive measures, such that the responsibily to correct issues lies only with the maintenance department and does not involve any other contributors to the production process, and firefighting in this way contravenes the notion of continuous improvement

Throughput Analyzer White Papers:

Meeting the Challenges of Manufacturing Success - It's Time for Less Data (December 2008)

Solving the Downtime Dilemma: 5 Reasons to Look Beyond Your Top 10 Downtime List (May 2008)

The OEE Deficit - Why It Can't Deliver the Results You Require (December 2007)