A systems approach
It is generally agreed among industry that a systems-based approach enables operations to be more efficient and sustainable.
Schematics of such systems are shown in Figure 1 for monitoring individual batches and in Figure 2 for monitoring batch-to-batch
variation (5–7). The systems underlying Figures 1 and 2 have the following characteristics:
Figure 1: Framework example for monitoring process stability and capability. ALL FIGURES ARE COURTESY OF THE AUTHOR
- Data are periodically collected from the process. Pharmaceutical manufacturing processes are often monitored using 30–60 minute
- These data are used to monitor processes for stability and capability using control charts, process capability indices, analysis
of variance, time plots, boxplots, and histograms.
- The analysis identifies when process adjustments are needed to get the process back on target.
- Records are kept on the types of problems identified. As significant problems are identified or problems begin to appear
on a regular basis, the resulting issues and documentation are incorporated into process-improvement activities to develop
Process improvement can be effectively completed using the define, measure, analyze, improve, control (DMAIC) problem-solving
and process-improvement framework (5, 6). The following section describes the tools typically used in this framework.
Figure 2: Framework example for monitoring batch-to-batch variation over time.
As a general principle, it is rare that a manufacturing process that is stable and capable will produce a product that is
out of specification. The primary purpose of a process monitoring system is to address the question: Is this process capable
of consistently producing product that is within specifications over time? The statistical analyses conducted to answer this
question are briefly described below. These methods are generally accepted and well documented in the literature (4).
A control-chart analysis is used to assess the stability of a process over time. The Shewhart chart has been widely used
to assess process stability since the 1930s. Other types of control charts are also useful for monitoring processes (4).
A stable process is a predictable process; a process whose product will vary within a stated set of limits. A stable process
is sometimes referred to as being in "a state of statistical control" (3, 4). A stable process has no sources of special-cause
variation—that is, effects of variables are outside the process but have an effect on the performance of the process (e.g.,
process operators, ambient temperature and humidity, raw material lot).
The most commonly used indicator of special-cause variation is a process that has product measurements outside of the control
limits which are typically set at X-Bar plus and minus three SD of the process variation for the parameter of interest (see
For example a process may be producing tablets with an average hardness of 4.0 kp and a standard deviation of 0.3 kp. The
control limits are thus 4.0 +/–3(0.3) for a range of 3.1–4.9. Any tablet sample outside of that range is an indication that
the process average may have changed and a process adjustment may be needed. Separate control limits are set for each parameter.