Quality Management

Ensuring product quality is one of the most important aspects of the work of any manufacturing enterprise. New equipment and a well-organized workflow are not enough for a modern enterprise to ensure consistent high quality of products. It is necessary to use statistical methods of production management. Their use allows an unbiased picture of the manufacturing processes to be seen and science-based results to be obtained. In addition, the use of such methods is a mandatory requirement of ISO 9001-9003 standards.

Scientific methods of quality management and control are based on a simple idea; models are built and plan figures are calculated on the basis of the manufacturing process data, sensor readings, processing parameter measurements, information about non-defective items production and so on. Subsequently, deviations from the expected results are analyzed. The presence of surges or steady trends point to the necessity to take measures for regaining control over the process.

Loginom contains all the necessary tools for developing quality management systems:

• Modeling. Loginom has numerous built-in modeling algorithms ranging from calculation of simple mean values to development of complex self-training models. The combination of different analytical techniques allows all the specifics of the manufacturing process to be taken into account, the influence of the diverse factors to be considered, and complex non-trivial regularities to be found.
• Outlier analysis. The tools available in Loginom make it possible to detect outliers in automatic or interactive mode, range them, check for overrun, and evaluate stability and volatility of the processes.
• Deviation visualization. The system offers numerous easy-to-use methods of data representation: distribution bar charts, diagrams, maps, trend lines. These allow the discovery of deviations quickly and with minimal effort and permit the detection of undesired tendencies at early stages.
• Finding out the causes of failure. The analytical mechanisms built into Loginom give answers not only to the question "what happened?" but also to "why did it happen?" These algorithms can extract regularities from large volumes of data and present them in the form of easy-to-interpret rules.
• Deviation alerts. If critical deviations are found, it is possible to automatically notify the persons concerned by sending them an e-mail or an SMS with a description of the problem and the information necessary to make a decision.

The analytical methods built into Loginom allow companies to maintain continuous improvements of the manufacturing process quality and to detect undesired tendencies and respond to them, model the development of processes, find out the reasons for defects and minimize the respective problems.