Process improvement is the deliberate optimisation of available process conditions and destra provides you with a rich set of statistical methods in order to do so. Statistical procedures test the statistical significance of different relations. destra also supports the application of simple statistical methods for process improvement, so-called Shainin methods.

Users benefit from an intuitive user interface and appealing graphics showing exactly the results they need.

Reliability study

Reliability analyses check whether a product meets its requirements under specific conditions over time. destra helps users to plan lifetime analyses, evaluate data collected in an experiment and shows the results in graphics.

  • End-of-life test
  • Censoring (type I, type II and hybrid censoring schemes)
  • Sudden death test
  • Eckel procedure for field failure
  • Success run tests

Design of experiments

Design of experiments is a tool for analysing cause-and-effect relationships between factors and responses and for optimising products and processes. A well-structured acquisition of data plays a major role.

  • Intuitive user interface to create individual experimental designs
  • Appealing and significant graphics of results
  • Optimisation of several responses

Variance/regression analysis

The analysis of variance and regression supports you in adapting mathematical models to cause-and-effect relationships between factors and responses.

  • Excellent model designs
  • Various designs for analysis of variance
  • Formula editor
  • Mixed effects
  • Hierarchically nested models
  • Unbalanced data
  • Visual model diagnostics
  • Cook’s distance, leverage values and residuals

Machine and process capability

A machine capability analysis provides evidence that the machines are able to produce specified product characteristics with required accuracy. After starting the process, operators measure further parts; these measurement results form the basis for preliminary process capability. In long-term process analysis, process results are illustrated based on distribution time models which in turn help to calculate short-term and long-term capabilities and to select suitable quality control charts.

  • Best suitable distribution time model
  • Quality control charts
  • Evaluation of results

Establishing process capability

Process analysis is based on statistical evaluations of characteristic values. The measurement process records these values. In order to avoid misinterpretations, the recorded measured values have to reflect the real situation with reasonable certainty. Various procedures and methods help to assess whether the measurement process is suitable for the intended purpose.


Udvidelser (Extensions)

The following functionalities are a perfect extension to the Q-DAS software product destra:

Form Designer

Q-DAS Form Designer makes it easy to create and modify available report templates. You may apply these templates in any Q-DAS software product. The interaction with M-QIS helps you adapt reports to the specific requirements of your intended recipients. Select from a tool box of texts, statistics, parts data, characteristics data and additional data as well as graphics (qs-STAT graphics and image files in the BMP, JPG, EMF and WMF format) and add links and logical operation formulas. Use drag-and-drop functionalities to position these elements in a report.

Overview (PDF 158 kB)

Serial interfaces

You may use procella to transfer measurement data directly via serial interface (RS-232). Here is an overview of available interface packages.

Overview of interface packages (PDF 116 kB)

Q-DM Datamanagement

The Q-DAS database forms the basis for statistical evaluations in qs-STAT. Only the database makes it easy to compare different information (machines, orders, etc.) and evaluate them automatically in M-QIS Engine.

Transfer of data

Q-DM is typically installed on a server in your network, sometimes even as a service. It monitors directories cyclically storing Q-DAS files. As soon as you store a file in a directory you Q-DM monitors, the systems saves its contents to a Q-DAS database. This process is based on defined rules you adjusted in Q-DM; these rules ensure a clear allocation of measurement information in the database.

You may adjust a wide range of settings, e.g. how to respond to alarms occuring while loading files in the database and store specific information to be considered in subsequent evaluations. The tool is able to generate protocols when a problem occurs while transferring data, e.g. due to a missing network connection or erroneous files and sends them to system administrators by email. The major task of Q-DM Datamanagement is to guarantee a smooth data flow.


In case your data are not available in the Q-DAS data format, you may apply a converter in Q-DM. It converts the foreign format into Q-DAS files and loads them in the database.

Overview (PDF 113 kB)

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