Feature Manufacturing Software 21st century management


Today’s manufacturers often struggle to effectively use the massive volume of data they collect. However, it is generally accepted that process-based manufacturing intelligence is the means to effective manufacturing enterprise management. Adept Scientific, European supplier of Northwest Analytics’ manufacturing intelligence and statistical process control (SPC) products, explain


tatistical process control (SPC) is a time honoured and well demon- strated method of process manage- ment. Everyone who has studied modern manufacturing knows of Dr Deming and his early work establishing SPC as a standard practice in post war Japan. SPC has long been used for mea- suring and monitoring quality by the quality departments and laboratories of most industrial manufacturing facilities. SPC has undergone periodic re-cast- ing and updates, such as Continuous Process Improvement (CPI) and Total Quality Management (TQM) and is now a key part of the Six Sigma and Lean Six Sigma programmes used by many manufacturers. Typical applications of the tradi- tional SPC methods include successful quality/process management functions


S


such as: ●


Routine SPC reporting.


● Process monitoring and improvement. ● Analytical method QC in laboratories. ● Regulatory compliance.


● Supply chain customer certification.


Real time operational decisions While SPC analytical methods have met the challenge of these functions, it is also the right tool for analysing other avail- able data. The time-based, com- parative analysis and visual presentation enables manufactur- ers to better understand their processes and, more importantly, take immediate action based upon resulting information. SPC is the appropriate technology and methodology to meet the current needs of manufacturing that call for


data analysis to provide: ●


maries and reporting. ●


● Measurement of ROI on systems. ● Timely and effective analysis sum- Predictive capability.


Identifiable benefits (lower costs, higher yields).


●


Support immediate actionable deci- sion processes based upon results.


●


High confidence to make process change for improvement.


●


Incorporation into a proactive process improvement programme.


●


Make it easy to get specific, role- based results for individual infor- mational needs.


16


Above: multi-variate SPC and stability analysis/shelf life prediction featured in Northwest Analytics’ NWA Quality Analyst Version 6.2


Right: Northwest Analytics’ NWA Quality Analyst


collects measurement samples in real time


●


Reduce complex calculations of aggregated data to meaningful and measurable information with context.


●


Immediately measurable results of actions taken.


If the demand is for better analysis, then real time, actionable, decision sup- port analysis are the rally points. Again, the SPC techniques, methods and charac- teristics lend themselves to these points and make more effective use of all the data in historians, MES and ERP systems. SPC also allows for the reduction of complex, specialised process data into graphic visualisations which opera- tions and management can quickly understand and take informed action. Some of the derived benefits of SPC-


based real time decision support: ●


Robust, easy to understand, high level of confidence.


● Identify, verify and reduce variation. ●


Analyses ongoing and immediate variation, not final product quality - process control not product control. ● Applies to both process and product.


●


Detects changes, shifts and unusual events.


● Separates signals from noise.


● Identifies causes of excessive variation. ●


Monitors real time results of continu- ous process improvement activities. ● Predictive problem detection on a


Provides documentation of compliance with customer supply chain requirements.


stable process. ●


SPC-based analytics Along with the demand for better data analytics is the desire to integrate production data and analysis with business data and analy- sis. This is the core concept of manu- facturing intelligence which provides a better understanding of complete corporate performance.


SPC-based manufacturing analytics is statistical and rule-based, providing the aggregation, analysis and role-based visualisation and reporting of manufac- turing data that enables users to better understand and improve their processes, identify and reinforce best practices, react quickly to process events and anticipate potential problems before they affect product quality, yield, or cost. What has been the result of the merg-


ing of these levels of business analysis and manufacturing analysis are value parameters used to monitor the overall status and performance of an operation. These are expressed as key performance indicators (KPIs), which are usually a single parameter consisting of an aggre- gation of financial, operational and mea- sured parameters to provide a meaningful KPI variable. These variables can be monitored using SPC via an easy to understand dashboard.


Manufacturing analytics methodolo- gies now enable a system to be created that monitors the stability and change of all the parameter components con- tributing to the KPI, which in-turn allows the detection of a change in one key KPI component before the KPI itself shows to be out of range. The visual presentation of this detection can be displayed not as just a ‘good’ (green) or ‘bad’ (red) status, but even as a ‘poten- tially getting worse’ (yellow) status. As a result operations and management can quickly identify, and even predict, early signs of detrimental change to take corrective action against.


Conclusion


Modern control systems, plant floor data collection and laboratories generate large volumes of process data. Unless this data is analysed and usefully reported to the staff involved in produc- tion and plant management it will not be useful for operational management deci- sion making. Using SPC and manufac- turing analytics enables this data to be effectively used to manage the enter- prise. Tightly coupled analytics will make control systems a core component of 21st century process and enterprise management systems.


Adept Scientific www.adeptscience.co.uk T: 01462 480 055


Enter 205 MAY 2013 Automation


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