Pythia by Visual Data Webservices

Pythia by Visual Data Webservices

About

The basis of Pythia are "Installations" and "Objects".

Within Pythia you create a model of your core production process.

Installations are the items of interest, and they consist of "Objects". Installations are the asset of your business. They can be latterly anything as far as Pythia is concerned.

 

Pythia; Process Behaviour:

Some definitions to start with:

  • Installation; highest level of the item of interest.
  • Object; Installations are build up from the constituent objects.
  • Parameter or Key Production Indicators; any measurement in an object that can be recorded by means of sensoring technique.
  • High and low tolerance; the values that define the highest and lowest measurement between the parameter measurement is allowed and valid.
  • Deviation factor; a percentage which allows the measurement to be offside of the “Event” value.
  • Behaviour; the total of measurements of all parameters in all objects that are in an installation.
  • Event (or Failure); Every failure is an event; but not all events are failures
  • Internal Object parameter(s); these are the parameters that can be influenced by the object itself like its operating temperature.
  • External Object parameter(s); these are the “environmental” circumstances that an object has to run in like the weather.

 

Pythia defines “Process Behavior” as the “Presentation of the process data during a certain timeslot”.

Pythia uses all kinds of data that is produced in a process during a certain timeslot. It takes the measurement and timestamp of a process parameter (like cooling temperature or pressure) and stores it in its database. Pythia combines the internal and external parameters to make it possible to take all possible causes in effect. All this information together forms the “Behavior” of an installation or object.

 

Pythia; Failures And Events:

In general, a failure is considered to be a "negative" event; it causes a "loss". All events are caused or triggered by one or more specific combinations of situations or states that is a system in. On the other hand; a positive event is a "gain". The purpose of the Installation.
Any type of production facility is thought of as being an "Installation". So, by generalizing this as a concept, it is possible to create a model of virtually every kind of productive organization, regardless the real (or virtual) product they deliver.

During production cycles, every installation facility is in any sort of "State". and the most important ones are closely monitored, because they are the main source of information that tells you whether the production cycle is "in control" and the produced goods are within acceptable quality standards. In general, most of this information data is gathered by sensors.

This brings us into the world of "Tolerances".

Tolerances are everywhere and always present. They are the mean measurement of "Quality" because they define whether a product, good or services is acceptable to be sold to always more demanding customers.
Tolerances have to ensure that all the produced goods are continuous, consistent and reliable without variances outside these tolerances.
But production processes have tolerances too! Within Pythia, every process parameter has its own tolerances, and these can individually be maintained.

The chain of production steps.

Customers regard a product as "Acceptable" when they receive their purchase within certain limits of acceptance. What these "Limits of Acceptance" are is greatly depended of the nature of the client, and the designated use of the goods they expect, buy or use. But the client is always the last part of the chain. This means that all the steps before that are due to influence the satisfaction of the client. Thus all these steps can be the cause of quality degradation in the eye of the client.

And this is the point that Pythia kicks in!

Every step in any production process can be identified as an (more or less) individual set of activities in the production system. And all these individual parts have their own "Key Production Indicators". These indicators are the items that define the "State" that this production step is in. And by guarding these indicators and by controlling their values (inside or outside tolerances), it is possible to ensure that every production step is performed well. But what happens when the quality of an outcome of a step is good, but the end control of the product says "NO!" Obvious there is a problem when individual production steps deliver results that appear to be good, but in the end turn out to result in poor end products.

Root Cause Analysis is the art of recognizing what is the cause and effect of any combination of "State" and "Event" (regardless good or bad) in any type of installation.

Because this application records all of the pre-defined "Key Production Parameters" (Internal and External) and also records all the failures or any deviation of produced products, it creates the possibility of analyzing the production steps from start to end, i.e. the behavior of the process.

Pythia; Pattern Recognition:

So what you do is select an "Event of Interest" and determine the number of parameter points that follow (to the right of the failure marker). 5 points are in general a good number to start with. In this way RCA makes it possible to detect certain issues, due to the fact that the combination of parameters lead to this failure. So, when you have selected an "Event of Interest", you have to create the pattern of, for example, 5 measurement points that go in advance of the moment of failure. Now you have to set up the pattern. This needs only to be done once for any "Event of Interest" and can be done as a function within the application by selecting the event, determine the number of pattern points (default=5) and the deviation factor (default= 10%) and then generate the pattern.

 

Pythia; Root Cause analysis:

Root cause analysis (RCA) is a method of problem solving that tries to identify the root causes of faults or problems. A root cause is a cause that once removed from the problem fault sequence, prevents the final undesirable event from recurring. A causal factor is a factor that affects an event's outcome, but is not a root cause. Though removing a causal factor can benefit an outcome, it does not prevent its recurrence for certain.

Because Pythia has all the relevant data in its database, it can present the analysts with the chain of events that preceded the “Root Cause”. The next manager in line can then take appropriate actions to solve the problem(s).

 

Pythia; Reliability Centered Maintenance:

Reliability Centered Maintenance (RCM) is a process to ensure that assets continue to do what their users require in their present operating context.
It is generally used to achieve improvements in fields such as the establishment of safe minimum levels of maintenance, changes to operating procedures and strategies and the establishment of capital maintenance regimes and plans.

With Pythia you can implement RCM to minimize maintenance costs. Pythia informs the maintenance officer that certain processes are at risk because the behavior of the installation, or even an individual object, is triggering a warning signal.

 

Pythia; Process Stability and Process Capability:

Process Stability and Process Capability are both extremely important aspects of any manufacturing process. Often the concepts behind process stability and process capability and the relationship between them are misunderstood. Pythia attempts to clarify the relationship between them. Defining Process Stability and Process Capability Process Stability refers to the consistency of the process with respect to important process characteristics such as the average value of a key dimension or the variation in that key dimension. If the process behaves consistently over time, then we say that the process is stable or in control.

Pythia offers all the necessary information to the management and process  analysts that is needed to determine whether the process is stable and/or capable.

 

Pythia’s Unique Selling Points:

Pythia offers a wide range of possible use by the way it operates on processes because it performs an in-depth data analysis on (big)data. It presents the results in the appropriate level of detail in easy-to-read graphics to the user with a specific interest and responsibility like:

 

  • Data analyst
  • Process analyst
  • Process developer
  • Risk manager
  • Quality manager
  • Maintenance officer

 

It offers functionality in terms of:

 

  • Root Cause Analysis
  • Process control and monitoring
  • Early Warning System
  • Quality control
  • Risk and damage control
  • Asset management
  • Risk Based Maintenance
  • Reliability Centered Maintenance
  • Pattern Recognition
  • Six Sigma analysis

 

Pythia in your organisation:

Pythia is an independent web based application. It takes the data by reading a text file (*.txt or *.csv) for either the operational data or the event occurrences and process these directly into the analysis per installation or object. These files can be output by any legacy system, as long as the record structure is maintained.

Warning messages are generated based on all kind of triggers and can be sent directly to any receiver’s mail address.

Pythia can be used for your own production process monitoring or as a service to your clients. Especially when your organization delivers maintenance services to other parties, Pytia can assist you by its early warning function even before your client knows that something is bound to happen!

 

Use Case:

Root Cause Analysis (RCA) is based on the combination of your registered production data for the parameters that are individually defined for any of your assets and the events that have happened on this object. Every event that is recorded (as an ”Event” or a "Failure"), will cause a red marker line in the objects data graphic. Due time a number of failure markers will appear, and you will be able to start an investigation on these data. Obvious, only events from the past can be evaluated. So the first pass is the periodically registration of both the production parameters and the events that happen. The actually RCA is to recognize certain patterns in the graphics (=production parameters). So what you do is select an "Event of interest" and determine the number of parameter points that follow. 5 points are in general a good number to start with. In this way RCA makes it possible to detect certain issues, due to the fact that the combination of parameters lead to this failure. So, when you have selected a " Event of interest", you have to create the pattern of, for example, 5 measurement points that go in advance of the moment of event or failure.

 

Benefits:

In short:

  • Cost reduction
  • Early warning system
  • Risk management
  • Maintenance management
  • Analysis tools
  • Ease of use

 

 

Groet, Greetings, Grüße,

Jos Richters.

Visual Data Webservices®
Visual Data Webservices®​Root Cause Analysis

 

mob: (+31) 630.432.284

tel: (+31) 546 - 454453

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