How to Use Manufacturing Automation to Cut Costs

How to Use Manufacturing Automation to Cut Costs

The term automation can be applied to any mechanism or device that moves by itself or is self-directed. Industrial automation uses a set of technologies such as PCs, PLCs, and PACs as well as various industrial communication devices and systems. Utilizing these technologies, we can automate a variety of industrial systems to control everything from liquid and air flow pressures to temperatures and flow rates efficiently and simultaneously. The backbone of an industrial automation system is its control system. A control system utilizes control loops to direct or regulate the behavior of other devices or systems. Closed-loop control techniques use feedback from sensing devices to ensure that process variables maintain and follow a setpoint. In addition to this basic functionality, an automation system can perform other functions such as computing setpoints, monitoring and reporting process performance, quality control, and equipment maintenance scheduling, among other tasks. In doing so, an automation system ensures that the manufacturing process is efficient and reliable, that downtimes are reduced, and that data reporting is accurate. The Beginnings of Automation and Impact on Manufacturing Production Costs The first known automated feedback-controlled mechanism that did not need outside intervention to operate was a float regulator for a water clock. It was invented around 270 BCE by the Greek inventor Ctesibius. The clock was the most accurate time-keeper of its day until the Dutch physicist Christiaan Huygens invented the pendulum clock in the 17th century. In 1785, American inventor Oliver Evens invented the first fully automated flour mill located near Newport, Delaware. Driven by waterpower, the mill is known to employ the first continuous industrial process. It reduced the need for human labor and increased the amount of flour that could be obtained from a given amount of grain. At a time when manufacturing production costs were mainly derived from labor, raw materials, and waste, Evens' invention was a game changer in that it significantly lowered the cost of production. Today's manufacturers have many more production costs and complexities to consider as part of the manufacturing process. They must comply with regulatory requirements and meet stringent product quality standards. Fortunately, the developments in automation have kept up with the times, and automation is now an integral part of the modern manufacturing business where it continues to be used to cut production costs. Facilities today use automation to quickly change batches or recipes, produce reliable process verification's, trace production data, and even track energy consumption. As advances in automation continue to dominate the manufacturing industry, some have voiced concern about the negative impact of automation on the future of human labor. I can personally attest that automating the manufacturing process is not all about replacing workers as some fear. Rather, it is about making workers' lives easier. I have been in manufacturing facilities that have a lot of automation throughout my career as a professional systems integrator. It is not unusual for an operator who is performing a manual task to ask me a question that usually goes something like this: "I hate this part of my job - is it possible to automate this?" Through reducing repetitive manual tasks, manufacturers can free up their workers to perform higher level operations. Thanks to advances in sensors, smart devices, software, and machine learning technologies, automation can streamline a manufacturer's production line and increase the production rate at the same time. It drives down the amount of product waste produced so that the product quality is maintained. Another critical benefit of automation is that it can be employed to reduce unscheduled downtimes. While many manufacturers forgo implementing this functionality due to the initial costs involved, I believe the ROI could be substantial. Employing automation to reduce downtimes could be as simple as programming a machine to watch the run-times on motors or to determine how many times a valve has cycled. The system could automatically send maintenance a message, informing them, for instance, when a piece of equipment on the production line needs to be scheduled for service. Alternatively, this process could be more complex and utilize sensors and software with machine learning and be employed to detect small issues like air leaks. Or, it could be more predictive, programmed to send out alerts to predict equipment failures within months, days, or even minutes. It's common to want to shy away from using automation for quality control within manufacturing and instead rely on human inspections and other manual quality control methods. The manufacturing industry still relies on human based quality control for a variety reasons, foremost among these is that it is still assumed that the human eye and human ability to pay attention to detail is far superior to a machine. However, with the current advancements in automation and vision systems, automated quality control now far outpaces human facilitated manual inspections. It is faster, more consistent, and more cost-effective. Machines do not have the weaknesses of their human counterparts - they do not suffer from fatigue or get lost in thought and make human errors. Thanks to the development of 2D and 3D vision systems, we can now inspect for product size, shape, and color, all without relying on human labor - the possibilities are endless. Even bar code reading vision systems now ensure the right label and packaging for a product is always displayed correctly and accurately without the need for human intervention. Long gone are the days of manual data entry. Operational excellence is now executed with real-time data acquisition. Manufacturers can quickly make changes to their production lines, reduce waste, and lower production costs. They can track customer complaints or quality issues back to their origin and resolve them faster and easier through data logging and historical data collection. Manufacturers can use the collected data to prevent future quality control issues and eliminate risks that might hurt their businesses (such as a product recall). Historical data can also be a useful tool for identifying bottlenecks on the production line.