In industry, operational inefficiency can cause catastrophic problems, resulting in unexpected shutdowns, missed deadlines, and eventually significant financial losses. These challenges are compounded by the lack of visibility and proactivity of traditional OEE (Overall Equipment Effectiveness) systems, which still predominate in many industrial environments.
One of the biggest challenges faced by industries is the lack of timely communication about operational problems. In traditional systems, production managers only become aware of machine failures or downtime if they are next to the machine or at the end of the shift, when it is already too late to correct the problem and avoid delivery delays. For example, a machine may stop unexpectedly, and the manager will only find out about it at the end of the day, making it impossible to recover the lost time.
Furthermore, processing machine efficiency (OEE) information using traditional systems is often manual and involves working with Excel spreadsheets to generate historical reports. This process not only consumes time but also increases the risk of human error, not to mention delays in problem detection. The lack of automation and proactivity in this process implies late identification of production delays and problems, with very low chances of reversal until the problem arises.
Another significant problem is the lack of contextualization of OEE data. Traditional OEE systems only measure machine productivity, without considering underlying factors that can affect efficiency, such as mechanical failures or maintenance issues. This prevents a complete understanding of the causes of OEE drops, hindering the implementation of effective solutions. For example, a machine may operate with low efficiency due to constant overheating, but because the OEE system does not monitor temperature, this root cause goes unnoticed.
One particularly problematic aspect is that OEE indicators are displayed on the machines themselves or on panels located at specific points in the factory. This requires the production manager to physically go to these panels to check the status of the indicators, a time-consuming process that can result in delays in responding to critical problems. In other words, if a manager or operator is not paying attention to the local machine panel, performance deviations indicated by the traditional OEE system may go unnoticed, risking delays in corrective actions. It is equivalent to "driving while looking in the rearview mirror," reacting to problems only after they have already occurred.
How do we solve the problem?
Many companies develop dashboards and solutions using third parties or their own IT department; however, these solutions are attempts to integrate a process that requires more than just a few integrated technologies. Furthermore, most of the time, these activities are deviations from the company's core business, impacting the workload of professionals with a solution that still fails to meet the expectations of production management.
The ideal solution should include an application capable of monitoring the variables of each machine on the production line in real time, cross-referencing information, and providing scalable, autonomous, and proactive alerts to those responsible. In other words, it should eliminate the need for physical presence or focus on any monitoring panel. In a simple and targeted manner, the system should send an auditable notification to users empowered to make decisions that prevent production line disruptions.
Furthermore, most problems encountered regarding equipment efficiency are effects of operational machine issues (overheating is an example discussed in this article). A system that simultaneously monitors operational machine parameters can provide process intelligence and alert the maintenance team before the problem affects production. This means treating the cause instead of the effect.
The biggest problem until now has been finding a solution capable of addressing all these issues without the prohibitive development cost.
Bridgemeter Solution: Proactive and predictive monitoring of machine health and operation.
The Bridgemeter from Above-Net was developed to overcome these challenges faced by industries, offering an integrated monitoring solution that goes beyond simply measuring productivity. With Bridgemeter, managers have access to a complete and contextualized view of production performance, including all operational parameters of the machines.
One of Bridgemeter's key features is its proactive nature. The system sends real-time notifications directly to the production manager's mobile phone, allowing them to monitor line efficiency without having to go to the information panels or equipment. This means that corrective actions can be taken immediately, minimizing downtime and preventing significant productivity losses.
Furthermore, the Bridgemeter monitors not only the overall efficiency of the machine, but also critical parameters such as temperature, pressure, and electrical current. With this integrated approach, it is possible to identify potential problems in advance before unexpected shutdowns impact production.
The flexibility and interoperability of Bridgemeter is another major differentiator. The system can be configured to adapt to the specific OEE needs of each client, seamlessly integrating with existing PLCs (Programmable Logic Controllers) or performing calculations after parameter collection. This flexibility allows Bridgemeter to be implemented in different types of industries and production configurations, providing a tailored solution for each scenario.
Furthermore, Bridgemeter offers an intuitive and easy-to-use interface that provides clear and actionable visualizations of OEE data. Managers can access real-time dashboards that display alerts about machine availability, performance, and quality, as well as overall OEE indicators. This facilitates informed decision-making and prioritization of corrective actions, continuously improving operational efficiency.
Results
Implementing Bridgemeter brings a number of tangible benefits to industrial operations. Firstly, the system's proactive nature significantly reduces unplanned downtime, resulting in increased machine availability and, consequently, increased production capacity.
Furthermore, the contextualization of operational data provided by Bridgemeter allows for a deeper and more precise analysis of the causes of productivity drops. This leads to improvements in performance and production quality, increasing overall OEE.
Bridgemeter's flexibility and interoperability with existing systems also facilitate its adoption, allowing managers to make more informed and data-driven decisions.
In summary, Bridgemeter transforms how industries monitor and manage the effectiveness of their equipment, providing a proactive, flexible, and integrated solution. Expected results include increased machine availability, continuous improvement in performance and production quality, and significant reductions in operating costs. By adopting Bridgemeter, industries can achieve a new level of operational efficiency and market competitiveness.
