Out of control processes in pharma manufacturing are not something to take lightly. If your production runs are seeing frequent deviations, leading to expensive batch losses or frequent rework, it’s time to take a look at ways to correct any process deviations in a more expedient manner. Uncorrected deviations or processes that vary from approved process parameters can lead to costly and dangerous mistakes.
Keeping your pharmaceutical manufacturing processes under control is important not only to ensure a quality product, but also for regulatory compliance. Process or raw material deviations can affect the downstream quality of a product and could mean tossing out an entire batch or end product if process corrections aren’t made soon enough — or if you can’t document that a correction was made before it affected your critical quality attributes.
For pharmaceutical manufacturers, a process deviation may not only mean a bad batch that affects a downstream process, it can also risk a regulatory violation that leads to fines or expensive market setback, or worse, it could endanger the health of the patient.
Most biopharma manufacturing companies are keen to adopt new methods that would streamline production, reduce errors and ensure product quality. That was the goal of Bristol-Myers Squibb when they implemented a complex real-time process monitoring system that involved integrating data from a number of different technologies, systems and vendors to gain greater control over complex batch processes.
In industries ranging from biopharmaceuticals to chemicals, executives in today’s manufacturing marketplace face ever-increasing pressures to grow profit margins, reduce time to market and optimize processes across all aspects of their business. Everything from constraints in the supply of raw materials to multiple steps in a manufacturing process can affect productivity—making process optimization an amorphous target.
Making the perfect bar of chocolate is not just about mixing the right amount of sugar and cocoa, or adjusting the process for product quality. Another factor that must be taken into account to optimize both taste and profits is the grinding time of the cocoa beans. Let’s take a look at how data analytics can be used to elevate both, and to find the right combination of ingredients and process to support the business goals — an important factor in the food and beverage industry.
In production, your media will pass several different refinement steps. To really understand and be assured about a good progression and state of the production, all of these processing steps need to be monitored continuously. With SIMCA® and SIMCA®-online, both part of the Umetrics® Suite of Data Analytics Solutions, you can confidently monitor and control every step of your process. The web clients allow you to access manufacturing data anytime, anywhere.
For manufacturing companies, process control is essential— even for those producing low-cost items such as small plastic parts. That’s because even when units are small and inexpensive, the cost of defects becomes exponentially higher when they reach the next manufacturing step at another plant.
All manufacturing industries need good control and good overview of their production processes. As already discussed in a previous blog post, SIMCA-online enables you to apply advanced multivariate data analytics in real time to monitor your production processes, for example to make sure that your production process is behaving as it should or that the quality is what it should be.
Using real-time data analytics monitoring has become the accepted way to monitor processes in several industries. The goal is to detect and diagnose issues as they happen, which is a great leap forward compared to traditional analysis conducted in retrospect. This has been highlighted in a previous blog post.
Using advanced data analytics models in real time opens up a whole new world of possibilities for improving your production processes. Not only does real-time process monitoring provide a level of confidence in your process performance, it can also help improve the overall quality of your production output.
The key to process manufacturing success is a mixture of knowledge and experience supported by mastery of data. A presentation I recently attended put this into sharp focus. A major paper manufacturer was faced with the challenge of maintaining paper smoothness during production. They approached this problem in a way that gave them enormous insight into their process, the ability to control it in real time, and ultimately lead to cost savings and maintained quality. There were also a few added benefits, including the ability to spot, diagnose and solve problems in real time.