How to prevent unplanned shutdowns in industrial plants

Unplanned shutdowns in industrial plants negatively impact plant operations. Long-term dependability projects, new technologies like artificial intelligence and machine learning and a reliance-centered culture can improve general equipment effectiveness and minimize downtime.

By Sanjib Das, PE November 15, 2024
Courtesy: Sanjib Das

 

Learning Objectives

  • Understand key strategies to prevent unplanned shutdowns, including predictive maintenance and application of new technologies.
  • Discover the typical causes of equipment breakdowns and how to handle them using a comprehensive strategy combining remedial and preventive actions.
  • Learn how to encourage a reliability mindset among staff members, the role training and ongoing feedback play in maintaining equipment conditions and the benefits of raising general plant dependability.

 

Industrial plant shutdown insights

  • Unplanned plant shutdowns can negatively impact production and reliability, but there are ways to avoid these problems.
  • Proper employee training, design planning and a proactive maintenance plan can all minimize unplanned shutdowns.

Unplanned equipment shutdowns present substantial challenges for industrial plants, negatively impacting production goals, supply chain reliability and overall competitiveness. Focusing on long-term reliability initiatives, leveraging emerging technologies and fostering a culture of reliability can minimize downtime and enhance overall equipment effectiveness. Key strategies include implementing predictive maintenance, tracking progress with relevant metrics and training employees to adopt a reliability mindset.

Figure 1: Unplanned shutdowns can severely disrupt industrial plant operations, leading to lost productivity, increased costs and reduced equipment lifespan. Courtesy: Sanjib Das

Figure 1: Unplanned shutdowns can severely disrupt industrial plant operations, leading to lost productivity, increased costs and reduced equipment lifespan. Courtesy: Sanjib Das

Reliable assets are crucial for meeting production targets in today’s competitive markets and a stable supply chain is essential for maintaining production flexibility. Companies increasingly leverage predictive technologies, such as artificial intelligence (AI) and machine learning (ML), for better asset control. These technologies provide greater management over equipment health, enabling companies to adjust production plans based on real-time data and business needs, ensuring assets are available and dependable, thus maintaining a competitive edge.

How equipment design flaws impact plant operations

Unplanned failures disrupt operations and lead to increased costs. Common root causes include:

  • Design flaws. Not addressing issues during the design phase can lead to equipment failures once in operation.
  • Installation errors. Mistakes made during installation can cause long-term reliability issues.
  • Improper maintenance. Neglecting proper maintenance protocols often results in equipment breakdowns.
  • Operational errors. Operating outside the equipment’s specified limits can cause premature failures.
  • Lack of training. Inadequately trained personnel may mishandle equipment, leading to equipment breakdowns.
  • Resource constraints. Resources often pull from long-term reliability efforts to address urgent issues, hindering improvements in overall reliability.

Addressing these challenges requires a holistic approach that integrates preventive and corrective measures. For example, industry data indicates human errors are responsible for approximately 80% of equipment failures, so ensuring proper training for maintenance staff can mitigate those mistakes. Adopting a rigorous design review process can identify issues early and reduce the likelihood of failures once the equipment is operational.

The impact of unplanned shutdowns

Shutdowns significantly increase workloads for operators and maintenance engineers, creating hazardous conditions during transitional startup and shutdown periods. Unplanned events necessitate root-cause analyses and firefighting efforts, stretching limited resources and sacrificing long-term reliability initiatives.

Shutdowns like these disrupt operations, increase costs and impact business sustainability and competitiveness. The additional workload includes preparing equipment for maintenance, isolating and flushing equipment and restarting processes, often leading to significant downtime.

Figure 2: Embracing a reliability-focused culture and following proven methodologies enhances general equipment effectiveness and operational success. Courtesy: Sanjib Das

Figure 2: Embracing a reliability-focused culture and following proven methodologies enhances general equipment effectiveness and operational success. Courtesy: Sanjib Das

Methodologies to combat plant shutdowns

Adhering to established procedures and operating within equipment limits are fundamental practices to prevent shutdowns. Key methodologies include:

  • Following procedures. Consistently adhere to established operational procedures.
  • Operating within limits. Ensure equipment operates within specified limits to prevent undue stress.
  • Training operators. Equip operators with comprehensive training to understand the broader system implications of their actions.
  • Early reporting. Encourage early reporting of abnormalities to catch potential failures before they escalate.
  • Feedback loops. Implement continuous feedback mechanisms to refine and improve operational procedures.
  • Design involvement. Include operators in the design stages to establish practical and accurate requirements.

Creating a proactive maintenance culture that promptly reports and addresses abnormalities is crucial to effective combat strategies. This involves fostering an environment where operators feel responsible for the health of their equipment, akin to a “reliability mindset.” Engaging operators in root-cause analysis sessions can provide valuable insights into operational issues and contribute to developing more robust maintenance practices.

Emerging reliability technologies and their place in avoiding shutdowns

Condition monitoring tools like vibration analysis, oil analysis, infrared technology and ultrasound are valuable for assessing equipment health, while efficiency monitoring tools track operating parameters over time. Technologies like DeltaV and Matrikon monitor process efficiency and historian tools such as Pi track operating parameters to identify trends. AI and ML can analyze data streams to provide insights into potential issues and actionable recommendations, enabling preemptive maintenance.

For instance, vibration analysis can detect early signs of bearing wear, allowing maintenance teams to plan repairs before catastrophic failures occur. Similarly, oil analysis can reveal the presence of contaminants that indicate internal wear, providing early warning signs of equipment degradation. Plants can develop a comprehensive view of equipment health by integrating these tools with AI-driven analytics and making informed maintenance decisions.

Measuring reliability improvement to minimize shutdowns

Tracking the effects of shutdown prevention initiatives requires metrics and key performance indicators (KPIs). Availability, performance and quality measurements are combined to assess how well equipment is used thoroughly: overall equipment effectiveness. Tracking the compliance rates of preventive maintenance (PM) enables plant managers to determine how well the maintenance plans are followed. This is essential to guarantee the timely completion of all required maintenance tasks.

Moreover, PM effectiveness evaluates the caliber and results of maintenance operations to ensure activities enhance equipment performance. Mean time between failures (MTBF) is another important metric that monitors the average interval between equipment breakdowns and offers information on the equipment’s dependability. Monitoring labor, material and overall ownership costs is essential to comprehending maintenance tasks’ financial effects and how to best use available resources.

How gathering employee feedback can prevent unplanned shutdowns

Creating a culture focused on capturing “as-found” conditions during maintenance and recording “as-left” conditions after changes are vital for ongoing reliability improvement. Training employees about the significance of this data and explaining the tangible and intangible benefits can make this practice spontaneous rather than a forced task. Tailoring messages for different groups, such as operations and maintenance, ensures employees clearly understand the importance of these practices.

Regular feedback sessions and workshops are instrumental in fostering a culture of continuous improvement. Encourage employees to share their experiences, observations and insights to recognize concerns early and develop effective solutions. In addition, involving employees in decision-making increases their engagement and commitment to reliability initiatives.

To illustrate the necessity of instituting these practices, consider the case of a foundry plant that faced recurring issues with a conveyor belt system carrying hot molds. The absence of coordination and data sharing among maintenance groups led to frequent failures. Implementing a reliability process involved short-term firefighting measures combined with long-term reliability initiatives like PM optimization and training. Prioritizing critical equipment and conducting detailed root-cause analyses improved MTBF from three to six months within a year, reduced costs and increased PM compliance from 30% to over 50%.

Explore the following sources to find detailed research and case studies on the benefits of prioritizing critical equipment and conducting root-cause analyses to improve MTBF, reduce costs and increase preventive maintenance compliance:

  • MaxGrip’s Reliability Metrics 101. This overview of MTBF’s importance discusses improvement strategies, including preventive maintenance and root-cause analysis. It highlights how these methods can lead to higher reliability and cost savings for organizations .
  • International Journal of System Assurance Engineering and Management. This journal features a study on risk-based maintenance approaches, emphasizing failure mode and effect analysis for prioritizing equipment failures. The study illustrates how these strategies can optimize maintenance processes and enhance equipment reliability.
  • Machinery Lubrication — Root Cause Analysis. This practical guide covers the essentials of conducting root-cause analysis, documenting findings and implementing changes. It provides real-world examples of how addressing root causes can significantly improve equipment performance and maintenance efficiency.

Establishing a process for planned and unplanned maintenance tasks based on engineering judgment further improved overall reliability.

Developing best practices for reducing equipment downtime

Implement these tactics to decrease equipment downtime and increase its effectiveness:

  • Focus on long-term reliability. Balancing short-term firefighting with long-term reliability initiatives is crucial. Consistent focus on long-term goals guarantees sustainable improvements.
  • Track progress with metrics. Relevant KPIs and metrics help organizations monitor their progress and make necessary adjustments to improve reliability.
  • Train and mentor employees. Fostering a reliability mindset across the organization involves training and mentoring employees to prioritize reliability as much as safety.
  • Avoid working in silos. Understanding the broader system implications of actions and promoting collaboration across different departments can prevent isolated decisions that may impact overall system reliability.

Ensuring equipment reliability in industrial plants is vital for operational excellence and market competitiveness. By balancing immediate problem-solving with strategic long-term planning organizations can significantly reduce unplanned shutdowns, cut costs and build stronger customer trust, leading to sustained operational success and enhanced market reputation.


Author Bio: Sanjib Das, PE, is an engineer with CMRP.