You're facing potential manufacturing process failures. How can you prevent future disruptions?

From what I've observed, proactive maintenance and regular audits are key. Implementing predictive analytics can also help identify weak points early, preventing future disruptions before they escalate.

1) Process Standardization: Develop and document standard operating procedures (SOPs) to ensure consistency. 2) Data Analytics: Utilize data analytics to monitor production processes in real time, identifying patterns that could indicate potential failures. 3) Continuous Improvement: Adopt methodologies like Lean or Six Sigma to promote ongoing process evaluation.

In manufacturing, most things that can go wrong have already happened or nearly happened. So in risk assessment, a historical review is very important. It has always amazes me how a team will hit a bump in the road and simply get up and go again without a thorough root cause analysis (RCA). Risk assessment, if it is thorough, will include a review of past RCAs

Quality control inspection and rigid testing. With proactive feedback both good and bad. Reinforcing good techniques and attention to detail

É fundamental uma avaliação detalhada por itens, antecipando possíveis paradas e emergências. Programar preventivas robustas e antecipar spare parts.

Preventive maintenance is probably the most misunderstood process in manufacturing. Production does not have confidence that maintenance can actually extend equipment life through planned maintenance events, and often defers to Run To Fail. The key word is preventive. In order for maintenance to prevent failure, it has to have access to the equipment to perform routine maintenance. Additionally needed is real time collection of equipment operational parameters, such as bearing temperatures and vibrations. And when maintenance is unplanned, it occurs when production needs the equipment. Idle time maintenance is not allowed, because production anticipates the need. In this scenario idle time is counted as up time, which is a lie.

Quando um plano de manutenção regular é realizado com o objetivo de antecipar possíveis paradas emergências, se consegue programar manutenção sem perda de produção.

Quality control is another misunderstood part of manufacturing. Quality control does not and can not control quality. Quality control is a component of quality assurance. Quality assurance uses quality control to measure the quality of the manufacturing process, but it can only find defects. Corrections are made as defects are found. Sample rates hopefully will identify deviations before moving past limits, but the better approach is to design processes to automatically stay within limits. It is impossible to inspect your way into quality.

O controle deve-se iniciar desde a matéria prima ate no cliente. Implementação de inspeção de qualidade, poka yoke durante o processo e armazenamento adequado.

Training is rarely applied to hands on operational processes. Yes, many will say, "we spend many hours of on the job training", but this training is just watching another worker perform his or her duties. This training rarely includes a job task analysis from which training objectives are derived. Someone may write down an outline of expected outcomes, but no actual training is included. In other words, there is no plan on how to get to the expected outcomes. And then the trainee is expected to sign the document so they can be held accountable when something goes wrong. Good training development an implementation requires a lot more than an outline of expected outcomes

Data-Driven Decision Making: Use data analytics to gain insights into your production process, identify trends, and predict potential disruptions. Historical data can reveal patterns that might indicate an impending failure. Real-Time Monitoring: Implement real-time monitoring systems that provide alerts if any aspect of the process deviates from expected parameters. This allows for quick responses to potential failures.