“All chance systems of causes are not alike in the sense that they enable us to predict the future in terms of the past”
Walter A. Shewhart
Today most of Pharmaceutical industries are struggling to get their processes in state of control and stable. The KPIs for the product monitoring mostly monitored through market complaints and Out of specifications. Organizations have developed the specification limits for the product by defining their quality attributes. Although organizations can get state of control i.e within specification but they are facing challenges to know about stability through statistical tools. SPC is a tool which would monitor your process with time and give a signal if any special cause variations are occurring in the process.Medical devices industries are using these tool frequently to monitor in-process as well finished products. I believe if pharmaceutical industries would start rigorously follow these tools market complaint won’t be their primary focus, because the variation would be surface prior to dispatch of finished products.
Statistical process control is a collection of tools that when used together can result in process stability and variance reduction. SPC is method of measuring and controlling quality by monitoring the manufacturing process. Quality data is collected in the form of product or process measurements or readings from various machines or instrumentation. The data is collected and used to evaluate, monitor and control a process. SPC is an effective method to drive continuous improvement.Before starting of SPC chart we must ensure measurement systems are in place.
Basic Principles
Variations exist in all process and can be categorized as
- Common or Random Cause Variations: A process that is operating with only chance causes of variation present is said to be in statistical control.This is inherent cause which we can’t identify and it is natural variation and unavoidable.
- Assignable Cause of Variations: A process that is operating in the presence of assignable causes is said to be out of control. Causes can be identified and eliminated.
Statistical Process Control also known as Process behavior Chart. Because it shows behavior of a process. There are few steps need to perform for making control charts. To identify appropriate control chart we must have knowledge about the data(nominal, interval, ordinal, ratio). Control charts are made depending on data category and subgroup size. Basically two kinds of SPC are made.
Variable Control Charts : deals with continuous data(measured in ratio data) X bar R, X bar S, ImR charts.
In statistical process control (SPC), the mean, range, and standard deviation are the statistics most often used for analyzing measurement data. Control charts are used to monitor these statistics. An out-of-control point for any of these statistics is an indication that a special cause of variation is present and that an immediate investigation should be made to identify the special cause.
Attribute Control Charts: deals with discrete data(defective/defects) follows binomial and poison distribution. P chart, nP chart, c chart, u chart
“The eventual goal of SPC is the elimination of variability in the process.”
A typical control chart has control limits set at values such that if the process is in control, nearly all points will lie within the upper control limit (UCL) and the lower control limit (LCL).
Rational Subgroup Sampling: Subgroups or samples should be selected so that if assignable causes are present, the chance for differences between subgroups will be maximized, while the chance for differences due to these assignable causes within a subgroup will be minimized. The basis of all control charts is the rational subgroup. Rational subgroups are composed of items which were produced under essentially the same conditions. The statistics, for example, the average and range, are computed for each subgroup separately, then plotted on the control chart. When possible, rational subgroups are formed by using consecutive units. Each subgroup’s statistics are compared to the control limits, and patterns of variation between subgroups are analyzed.
Selection of Control Charts
Control Chart Analysis: To analyze the control charts it is important to remember that the data is represented over six standard deviations, there are three standard deviations from the mean line to the upper control limit and three from the mean to the lower control limit. To help analyze the charts, it is important to divide the chart area into six zones A, B, and C representing the standard deviations.
All about Pharmaceuticals & Medical Devices 
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Thanks ghe .Honestly appreciate your feedback.I will incorporate in future topics
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