In the era of increased automation, a yawning gap often exists in the training cycle for standard line manufacturing production operators, who often find themselves caught in a “neither here nor there” loop of skills accruement that leaves them familiar yet not wholly proficient. This disconnect can be remedied through integrating continuous improvement tools into equipment training agendas.
Training, by its very nature, is a trial and error process that can yield wide-ranging results when ramping up new manufacturing operators or building cross-functional skills within an organization. It is, quite simply, nearly impossible to replicate all real-world scenarios in training sessions; not all training provides the solution for every problem. Eventually, operators must face and ultimately overcome obstacles in the sink-or-swim value stream of equipment downtime.
Upon experiencing such downtime, management tends to bend back toward training, an arc that, for operators, spurs a tenure-long loop of pre-acting and reacting. Following the initial cycle of understandably incomprehensive training (since there is, really, no such thing as comprehensive training) and inevitable equipment downtime, an organization might respond by adding resources and scenarios to training sessions to prevent a similar situation from causing more downtime. But of course, a different situation then arises back in the value stream. Rinse and repeat.
As more and more “baseline” operations becomes increasingly automated, the concept of hierarchy also comes into play. The balance between training entry level manufacturing operators on technical equipment functions versus reserving such knowledge for maintenance technicians continues to be a challenging aspect of manufacturing in many industries.
Typically, training for standard entry level equipment operators is just that: standard. The chief priorities at this lowest rung are mostly intended to ensure an operator’s functional working knowledge of relevant and ancillary manufacturing equipment, as well as all critical quality and compliance standards. And this factory line approach has its benefits, as segregating expertise allows production machinery operators to focus on their specific tasks at hand, a stage-centric mindset that has combined efficiency and effectiveness – i.e., speed and customer satisfaction – since Henry Ford first built Model Ts in such novel assembly-line fashion.
But especially in specialized, highly technical settings such as modern pharmaceutical production environments, at times operators are faced with problems they have not seen before or do not possess the education or technical skills sufficient to fully understand and therefore resolve. The result is unacceptable products, equipment inefficiency, or varying degrees of both.
The reaction from management might be to add more people to the process, or supplement the line operator with additional automation such as vision inspection systems and higher-level computerized feedback mechanisms. Here, there are immediate goals in mind, predominantly meeting short-term production goals (which now may include making up for lost product and equipment downtime).
Unfortunately, the interventionist steps taken – personnel, machine-based or both – add extra steps in the manufacturing process and, closer to the topic at hand, additional training for one or more operators, adding cost and manpower to a problem that, had it been handled differently from the outset, may not have required as much of either precious resource.
In this manner a typical machine operator, who started on the line manually checking product, adjusting fill weights and loading packaging components, now finds himself immersed in machines that are making decisions for him at a faster pace, or teamed up with additional team members who might best be utilized elsewhere.
In most circumstances the aim is to enhance the line through automation. Equipment training at the operator level is planned into (and an integral share of) the installation and qualification process. This approach leaves operators with a general understanding of machine function and set up and, with some equipment manufacturers, also a review of minor troubleshooting techniques. Only on rare occasions does this initial training prepare an operator for an unexpected event, and in many cases such unforeseen occurrences are not referenced in the troubleshooting guide or tech manual.
This is where a continuous improvement approach toward training can enable an operator to take the mechanics and technical capabilities of the equipment and build upon them to broaden his understanding and arrive at a thought-based situational-specific response. This approach enables the operator to build trending data, develop knowledge of likely root causes and, ideally, recommend technical solutions to the engineering staff. The overall performance is enhanced not only by building individual confidence in responding to equipment downtime situations, but also by reducing overall losses in several areas within the value stream. This approach also frees up technicians to be utilized in other, assumedly higher-level areas.
Workforce expectations for entry level production operators are usually quite low, and tied into the understanding that technicians are compensated for higher-level skills – namely, ones that expediently resolve line equipment problems and execute perpetual preventative maintenance programs. Though no one would argue with the need to have talented techs on standby, some problems can be resolved easily with few technical adjustments.
These situations are as varied as production execution itself. For example, in some cases there are problems that operators are aware of but, by striving to maintain production output, chose to run production at a slower pace to compensate rather than stop the line entirely. Here, two factors are at play. One, operators are generally reluctant to notify technicians in instances they deem problematic but non-critical. Second, they are basing their decisions on past practice; when the technician arrives at the line, the technician will be charged with ironing out the kinks to recommence full production speed. That’s simply the way it’s always worked.
Of course, the downside to this force of habit is obvious: upon arriving, the technician essentially must “relearn” the problem from the operator in a time-consuming game of telephone. The ensuing course of action often results in production stopping altogether or, at least, with product rejected from the line during troubleshooting and adjustments made to improve the situation. If the problem is large enough, it could result in scheduling overtime to complete the customer order.
In this scenario, the technician is vested in fixing the equipment, while the operator’s main concern is completing the customer order. The partnership ultimately shares the same goal – to produce quality products – but have separate approaches.
An example of this can be found in label application. Labeling applied at higher speeds requires greater accuracy, as packaging placement is critical to ensure product quality specifications are being met. Due to a physical abnormality in any number of factors impacting this process, for a particular product run problems arise in a wrinkle. When the line is slowed down, the problem is not as frequent or eliminated but the technician would be called out to address the problem. Upon arrival, the technician recreates the problem by increasing the line speed, thus product is rejected; the problem is rarely identifiable at first glance. The line runs through a series of stop and start gyrations until the decision is made to start adjusting; at this point adjustments improve the situation but do not completely resolve it. The next step is to identify potentially worn parts and begin the replacement process. The line is shut down, with all the attendant consequences of delay, cost and risk of customer dissatisfaction.
The operators in this example were trained in label application and fully understand set up and equipment function. But a trained operator has a gap in knowledge between equipment understanding and technical solution. If this operator were trained in the beginning on a thought-based situational response, they would be able to apply a technical recommendation enabling the technician’s repair time to decrease significantly.
In this example the operator would use trend data to further broaden the wrinkled label problem to make it more identifiable. They then apply a “five why” approach – a method of asking “why did this happen” to a cascading set of factors until a likely origin is revealed – to dig deeper into understanding the issue’s root cause. The findings indicate the problem was attributed to bottle wall thickness; the label’s leading edge would not adhere at high speed to a soft-sided bottle, resulting in a wrinkle.
This example demonstrates a deeper sense of understanding production equipment technical functionalities, and reinforces operator confidence in helping produce a sound solution within a consolidated timeframe.
Understanding typical operator level problems by implementing a continuous improvement process into equipment training also improves management’s ability to identify minor problems that may occur over time but lend themselves to a significant amount of downtime.
A good example here is the upkeep of filters for air collection and evacuation systems, which require periodic cleaning. These are normally found on a preventive maintenance schedule. However, in one case, the system pulling powder product to the filler delayed less than a couple minutes. The operators were aware of the problem, and it only resulted in minor production stops… but these minor stops added up, eventually encompassing the highest percentage of downtime the line was experiencing. By the time a month had passed, a full shift’s worth of work had been sacrificed.
The problem persisted until downtime reporting data was pulled. The operator confirmed the stoppages’ frequency and recommended that, for particular products, that a more frequent filter change occur. The technicians were involved in the process and supported the resolution. The partnership functioned more fluidly from problem identification, resolution recommendation and solution implementation.
Pharma manufacturing processes are becoming increasingly technical to maintain customer demands for speed to market and reduced production costs. Too often, these challenges result in a loop of entry level equipment training, new equipment updates, unnecessary downtime and fixes that either slow processes down or add resource-driven costs.
In this environment, manufacturing operators will continue to be crucial to optimized plant performance. Training operators to develop thought-based situational responses by broadening their equipment training through continuous improvement methods offers the best chance for the sophistication of operators to grow along with that of the machinery they are operating.
Author Biography
Mike Greene is Union Facility Plant Manager for Pharma Tech Industries, a leading contract manufacturer to some of the world's most trusted health and wellness brands. The company’s cGMP service offering includes manufacturing, packaging, injection molding, technology transfer, project management, process and packaging development, and quality assurance testing. Mr. Greene has over a decade of experience overseeing supply chain and operations processes.