10 Continuous Improvement

The U.K. railway network dates back to 1825 and is the oldest railway in the world. Several electrical assets on the network such as track power cables, switchgears, overhead line isolators, circuit breakers, and insulators are beyond their design life and the business must decide whether to renew or replace them—even though they're still operating at the optimum performance level. These assets are still being maintained at the original regimes; the challenge to the business is to understand the degradation models and change them to achieve different maintenance regimes for the aging assets. The work we're currently undertaking is intended to influence and change our asset policies—in particular, the assignment of asset regimes for assets that remain in service at the end of their design life and beyond. The philosophy behind the maintenance regimes is that they're based on degradation models, which are algorithms that consider various factors such as the environment, the loading, the utilization, the reliability, and the cost for interventions. The approach we pursued was to review the parameters of the degradation models for their “fit,” based on the knowledge asset managers have gained on the ground and through large volumes of asset data. The asset data was analyzed with data visualization software to gain further insight to influence the review of the degradation models. The findings of the work are summarized here: asset population is aging and future renewals bow wave are predicted; asset policy pushes all assets to maximum asset technical life and fix-on or run-to failure; safety-related works prioritized over asset performance/resilience; there's a need to modify some factors associated with the degradation models to cater for extension of technical asset life and maintain a more realistic/sustainable asset renewal profile; composite asset condition scores are required to manage bow wave of asset renewals and implement sustainable obsolescence management techniques (this is predominantly driven by organizational investment decisions where enhancements are the main driver of asset acquisition, making future renewals difficult due to the requirement to renew similar age assets at the same time); and determination of useful asset life required for assets that are being left in service longer than their originally predicted life.

Learn to build a business case for improvements in Maintenance at your operations. You know your maintenance performance can improve, you know the problems you are faced with, you know some of what to do to correct it, you know it will take effort and some investment, and you need to prove it is worth investing in to your senior management / executive branch. To make the case, you need to show what it can save or earn for your business - where you will see the payoff and you need to estimate the cost of the investment. This is a hand's on workshop. Bring your maintenance performance metrics and be ready to work. You will be shown useful benchmarks that can be used and how to use them. Using those and the metrics from your current state you will show the potential benefit of making changes. After working out the potential benefits we will discuss tips for getting support and making your case an easy sell.

Any plant, in order to maximize its production, must have a world-class maintenance team that takes care of every single piece of equipment in the field. Maintenance teams could be considered the superheroes of any plant, since they must always maintain and return the equipment in the fastest and most efficient way. Wrench time is the actual time a maintenance crew works on a piece of equipment, and wrench time analysis is used to measure the maintenance team's effectiveness. Many companies apply wrench time for a very limited time and do not go for a continuous way of study. This presentation will show a self-reporting wrench time case study that was implemented in a Saudi Arabian petrochemical plant. We'll aim to explore the effect of self-reporting wrench time and answer the following three questions: Does wrench time analysis increase maintenance efficiency? Does self-reporting wrench time lead to better maintenance efficiency? What is the impact of self-reporting wrench time on maintenance team performance?

Metrics, best practices, more than 40 key elements to implement, challenges, and opportunities all combine to make a successful implementation difficult. Where do you start, and how do you know how to work on what matters? Once you understand how it’s all related, you can focus on the vital few to leverage the maximum ROI. This presentation will clarify the importance of culture and employee engagement, along with other key plant floor performance indicators that will be clarified with data. We'll look at the current state of R&M; what’s working and what's not; survival skills for the next decade; impacts of connected technologies (edge computing, big data, machine learning, AI, 3D printing, augmented reality); the importance of getting your data ready for what's coming next; and relationships between R&M and safety, people engagement, quality, throughput/uptime, and cost.

This case study will show how we used an analysis of standard work management metrics and a systematic approach to identify opportunities to improve our plant. We'll provide specific examples of how we developed and implemented the approach and the results we achieved. We'll also describe the fundamental understanding and steps that could be taken to implement a similar approach at any plant, or for any particular metric. Topics will include cultural recognition of KPIs as an improvement tool, not a personnel measurement stick; understanding all the various causes and influences on any particular metric; analysis and categorization of deviations; identifying losses as acute one-offs vs. chronic systemic issues; behavioural vs. procedural issues; understanding change/improvement requirements, what can be directly controlled and what can be only influenced; determining corrective actions; and tracking the resulting improvements. Specific examples will be derived from our site's application of this methodology to schedule compliance, PM/PdM compliance, and emergency work metrics.  

Reliability Centered Maintenance – Reengineered, provides an optimized approach to a well established and highly successful method used for determining failure management policies for physical assets. It makes the original method that was developed to enhance flight safety, far more useful in a broad range of industries where asset criticality ranges from high to low. RCM-R® is focused on the science of failures and what must be done to enable long term sustainably reliable operations. If used correctly, RCM-R® is the first step in delivering fewer breakdowns, more productive capacity, lower costs, safer operations and improved environmental performance. Maintenance has a huge impact on most businesses whether its presence is felt or not. RCM-R® ensures that the right work is done to guarantee there are as few nasty surprises as possible that can harm the business in any way. RCM-R® addresses the shortfalls of RCM that have inhibited its broad acceptance in industry. Little new work has been done in the field of RCM since the 1990’s, yet demand for such a method, better adapted to industrial applications is higher than ever and growing. Demographics and ever more complex systems are driving a need to be more efficient in our use of skilled maintenance resources while ensuring first time success – greater effectiveness is needed. RCM-R® was developed to leverage on RCM’s original success at delivering that effectiveness while addressing the concerns of the industrial market. RCM-R® addresses the RCM method and shortfalls in its application. It modifies the method to consider asset and even failure mode criticality so that rigor is applied only where it is truly needed. It removes (within reason) the sources of concern about RCM being overly rigorous and too labor intensive without compromising on its ability to deliver a tailored failure management program for physical assets sensitive to their operational context and application. RCM-R® also provides its practitioners with standard based guidance for determining meaningful failure modes and causes facilitating their analysis for optimum outcome. It places RCM into the Asset Management spectrum strengthening the original method by introducing International Standard based risk management methods for assessing failure risks formally. RCM-R® employs quantitative reliability methods tailoring evidence based decision making whenever historical failure data is available.

As always, equipment maintainability plays an important role in uptime. Besides the reduction of failure rates, the quick recovery from those failures or the successful execution of scheduled activities makes a considerable difference in availability indicators. The application of Lean tools and Six Sigma analysis contributes to the improvement of maintenance execution by applying the 5 steps of Lean Six Sigma methodology (Define, Measure, Analyze, Implement and Control) and using the tools associated with them. This webcast will discuss Lean Six Sigma theory, basic principles of the methodology and case studies showing the use of tools. Case 1 will illustrate the application of Lean Six Sigma in scheduled preventive maintenance for slurry pumps operating in the oil sands industry. Case 2 will examine how the use of Six Sigma analysis reduced the corrosion rate of tubes in a bank of 12 heat exchangers shell and tube type, which heat diluted bitumen upstream of a distillation tower. Both cases emphasize the importance of using data and facts to make decisions, including front end personnel, and the sustainment of implemented solutions.

KPIs are often used to measure the past performance of a process, but did you know that they can be used to see into the future and predict the performance of the organization?KPIs can be used to measure past performance, or predict future performance. This is because there is a cause and effect relationship between leading and lagging KPIs. When a process is measured, it will in turn effect another process which is also being measured, providing insight to future performance.When Leading and Lagging KPIs are properly understood it provides unique insights to where the performance of the organization is going.

By using Root Cause Analysis you can end the re-occurring issues that arise in your plant.  Root Cause Analysis is used to determine the underlying cause or causes of a failure so that steps can be taken to manage those causes and avoid future occurrences of the failure.Performing a Root cause analysis can be a quick simple task or a in depth difficult task depending on the complexity of the issue being addressed.

In 2017, the LINK Automated People Mover (APM) at Toronto Pearson International Airport transported an average of 24,000 passengers per day — a 20% increase in passenger traffic from 2015, according to a 2017 report by the GTAA. To increase operational service levels, preventative maintenance optimization (PMO) initiatives were undertaken in 2015 and 2016 in co-ordination with the APM owner, manufacturer, and O&M service provider. The initiatives were designed to increase the overall day-to-day operational run-time of the LINK system while maintaining existing levels of safety and reliability. In this workshop, we’ll use the LINK APM system as a case study to discuss the requirements for successful PMO implementation, which include interorganizational communication and co-operation, RCM strategies, and due diligence as it relates to safety-related subsystems and processes. We’ll also offer a blueprint for similar optimization strategies.