Data-Driven Machine Inspections & Results

Join us for an enlightening webinar titled “Data-Driven Machine Inspections & Results”. This session aims to spotlight the significant influence of data in machine inspections and its overall impact on informed decision-making processes.

We will explore the necessary techniques to break down data silos and encourage seamless data flow across your organization. The webinar will also emphasize the importance of data-driven decision-making over emotionally charged decisions, leading to reduced risk and enhanced efficiency. Additionally, we will address the common pitfall of analysis paralysis, guiding you toward a more streamlined decision-making process.

While we intend to discuss result optimization in a future session, this webinar’s primary focus is to establish a strong base on the significance of data and its effective utilization in machine inspections.

Key Takeaways:

  1. Strategies to Break Down Data Silos: Learn the tactics that can help you dismantle data silos, leading to a free flow of information and data across different departments in your organization.
  2. Data-Driven Decision Making: Understand the power and reliability of data-driven decisions over emotional ones. Discover how data can reduce risk and boost efficiency in your operations.
  3. Avoiding Analysis Paralysis: Acquire strategies to evade the trap of over-analyzing data to the point of inaction. We will guide you on how to make effective and timely decisions based on your data analysis.

We welcome you to seize this opportunity to gain valuable insights from industry experts that could revolutionize your data-handling processes. Looking forward to your participation!

Harnessing the power of data can revolutionize the way we approach inspections, leading to improved outcomes. Without data, we often rely on emotional decision-making, which can be detrimental and counterproductive. That’s why this webinar delves into the essential elements necessary for leveraging the data we already have and uncovering any gaps in our systems and processes. Together, we’ll explore step-by-step actions, what needs to be done, and why it’s crucial for your success. The ultimate goal is continuous improvement, as we strive to achieve better results. So, let’s embark on this journey of data-driven insights and elevate how we conduct machine inspections.

Why Should We Prioritize Data-Driven Decisions?

Without a structured process in place, we run the risk of making less-than-optimal business choices. That’s where the field of behavioral economics, championed by Nobel laureate Richard Thaler, comes into play. Thaler’s research challenges the assumption that humans consistently act in their best interest. To illustrate this, he once hosted a dinner party and noticed guests devouring cashews before the main course, potentially ruining their appetites. Wisely, he removed the cashews, which resulted in the guests expressing gratitude.

This seemingly irrational behavior defies traditional logic – denying someone an option shouldn’t make them better off. Yet, we’ve all experienced situations where we’re thankful for someone removing tempting treats or taking away a cake we couldn’t resist. Whether it’s related to weight loss, smoking cessation, equipment maintenance, or any other goal, we often find it easier to check a box than to go the extra mile for long-term benefits. This is where data-driven decision-making comes in, guiding individuals toward the desired actions and outcomes. Instead of simply noting that a motor is running at 240 degrees Fahrenheit, the focus shifts to troubleshooting, fixing the issue, and driving tangible results.

What are the Types of Data?

In the realm of maintenance, we encounter:

  • Subjective Data – revolves around personal perceptions and feelings.
  • Objective Data – provides us with concrete numbers and measurements.

To illustrate this, let’s consider a precision maintenance form crafted by Chris. When it comes to objective data, we rely on hard numbers – the indisputable facts. We establish limits and set thresholds for error. For instance, if a motor is running above 160 degrees Fahrenheit, it triggers a flag, prompting us to take action. On the other hand, subjective data captures our perceptions and asks for assessments based on experience. We classify things as pass or fail, determining their overall condition. If something fails, we immediately identify the call to action. This is where automation, such as handheld devices, can be incredibly valuable, guiding us in making informed decisions.

Alongside subjective and objective data, there exists a myriad of other data types to explore. However, it’s crucial to acknowledge that there are situations where waiting for hard numbers isn’t feasible. If you experience chest pains shooting down your arm, you wouldn’t rely solely on data – you’d prioritize immediate action, heading to the hospital for a thorough check-up. So, as we navigate data types, remember their diverse applications and the critical role they play in decision-making processes.

The Purpose of Machine Inspections

When it comes to machine inspection, the true purpose and their significance in the world of reliability go beyond simply checking off a task. Merely completing the inspection without addressing the identified issues is not enough. It would be the most expensive type of inspection, where all the effort goes into collecting data, only to have the machine fail later on. Instead, at its core, the purpose of an inspection is to detect the early signs of failure. It’s about proactively identifying potential functional failures and breakdowns and taking action to fix them before they occur. Whether it’s through visual observations, listening for unusual sounds, or feeling for irregularities, inspections serve as a crucial tool for identifying potential issues. It doesn’t matter who is conducting the inspection – mechanics, operators, specialists, or managers – the goal remains the same: to uncover problems and take action to get them fixed.

This aspect of inspections holds immense power when it comes to launching a successful reliability program and engaging people in the process. The ability to address and resolve issues promptly becomes the pivotal leverage point that drives reliability and ensures the smooth functioning of equipment and systems. So, let’s recognize the vital role inspections play in keeping things running smoothly and embrace their importance in our pursuit of operational excellence.

How Are You Collecting Data?

Picture this: you’re conducting an inspection and you start noticing certain results that catch your attention. Maybe you discover sprockets that are worn on one side, prompting the sawmill to rotate them for continued use. Or perhaps you spot a machine that appears fine from the surface, but upon closer inspection, you realize it’s sitting on a rusted foundation that could spell disaster in the future. Then there’s the motor with a mix of carbon steel and stainless steel shims, bent and corroded washers, and a troublesome jack bolt. All these findings beg the question: What’s the next step?

Imagine if you had all this documented and readily available for the next time you work on that machine. It would be truly fantastic, right? But here’s the catch: if it’s all scribbled on a piece of paper, what are the chances it will be shared or transferred into the work order system? This is where we often find ourselves in a data desert, devoid of any meaningful information. Alternatively, we might encounter a data mirage, where we think we have the data but struggle to access it when we need it most.

But what we truly aspire for is a data-rich environment, where we have an abundance of valuable information at our fingertips. This is the ideal state, where we can make informed decisions and take proactive actions to prevent failures. Remember, even visual inspection is a form of data, and it’s crucial to harness and utilize it effectively to be data-rich, not data-deprived, and seize the power of inspections to drive reliability and success.

Common Data Collection Challenges

Let’s dive into a scenario where subjective inspection data holds crucial insights. Imagine a group of operators inspecting a hot oil machine. They diligently observe and document the various defects they come across. As you look at the inspection report, you notice 15 notable issues, and some of them raise serious concerns. High vibration, a missing foot bolt, hot oil leaks, an open conduit, and the absence of a grounding strap – all of these combined create a worrisome picture. These conditions could potentially lead to disastrous consequences, and that’s definitely not a good situation to be in. Now, let’s pause and think about the chances of this handwritten data making its way into a comprehensive work request. Unfortunately, the likelihood is slim.

But what if we had a better system in place? Imagine if the inspection was carried out using a tablet or a digital device that could capture all these 15 items instantly and seamlessly transfer them into a work notification. Now, we have a list of actionable items that can be addressed promptly. While we might not fix everything right away, we can prioritize tasks like adding a grounding strap, addressing the open conduit, and resolving the hot oil leaks to improve safety and prevent further damage. This is the kind of inspection data that holds immense value, especially when we transition from the limitations of pen and paper to a digitally empowered approach. By leveraging technology, we can stay ahead of the competition and bridge the gap between potential risks and proactive solutions.

The Role of the Inspection Cycle

The first step is to inspect and identify the signs of failure. That’s the foundation of the process. Once a failure is spotted, it’s time to take action. This is where work notifications come into play. The identified issue is documented and communicated to the appropriate channels. From there, the planning and scheduling phase kicks in. The repair process is initiated, and cost avoidance is tracked to ensure optimal outcomes. Once the repair is complete, it’s time to rinse and repeat the cycle for ongoing maintenance and improvement. 

Now, let’s address an important aspect: the distribution of responsibilities within an organization. In many cases, the task of identifying work falls on everyone but the maintenance team. Maintenance’s primary focus is on fixing, repairing, and improving. Consider this: what would you want your maintenance personnel to be doing? Is it fixing the existing backlog of identified work, which could keep them busy for the next couple of decades? Or should they be out there, actively identifying new areas for improvement? It’s essential to acknowledge the limited resources available and the opportunity cost associated with their allocation. 

So, how can we engage operators, predictive maintenance groups, and all other stakeholders to participate in the inspection process? The goal is to have maintenance personnel concentrate on what they excel at, fixing and improving while ensuring systems are operating at peak precision. To achieve this, we need to create a seamless collaboration. Operators become instrumental in identifying failures, while maintenance swiftly eliminates them. By dividing responsibilities effectively, we can leverage the expertise of each group and add the most value where it’s needed. Ultimately, the key lies in streamlining the workflow and engaging all parties in a synchronized effort.

Steps to Achieve Data-Driven Inspections

Create an Accurate Asset List

To make data-driven inspections a reality, we need a solid foundation: an accurate list of assets. This might sound like a simple task, but it holds immense importance. Without a comprehensive and up-to-date inventory of assets, your progress will be hindered, and you’ll find yourself navigating through a sea of challenges. 

So, what can you do to ensure success? Asset mapping is the key. It involves physically walking through your facilities, examining and documenting each piece of equipment. You’ll uncover vital details such as machine types, unique IDs, and precise locations. This information is the backbone of effective asset management. It empowers you to make informed decisions, streamline processes, and optimize maintenance strategies. Think of asset mapping as the starting point of your data-driven adventure. It sets the stage for a more efficient and organized approach to managing your assets.

Determine Equipment Criticalities

Once you’ve successfully mapped out your assets, the next step is to determine their criticalities. But what exactly does that mean? Well, it’s all about understanding the impact of each asset’s failure on your business operations. If a particular machine or asset goes down, how does it affect your overall productivity? 

Here’s where the concept of criticality comes into play. We assign a numerical value to indicate the level of importance or criticality of each asset. This helps us prioritize our maintenance efforts effectively. By knowing the criticality of an asset, we can make informed decisions about what needs immediate attention and what can wait.

Let’s face it, not all assets are created equal. Pareto’s rule comes into play here, stating that roughly 20% of your assets will be the most critical ones, requiring in-depth analysis such as failure modes and effects analysis (FMEA). For the remaining 80%, you can assemble a cross-functional team and utilize FMEA tools to assign criticality ratings. The key here is not to obsess over being 100% accurate, but rather to establish a relative ranking system. This way, you can identify and prioritize the machines that hold the greatest significance for your business. By focusing on the critical assets, you ensure that your maintenance efforts align with your business goals and maximize overall operational efficiency.

Optimize Asset Bills of Materials (BOMs)

Once you’ve identified the critical assets, it’s crucial to ensure they have accurate bills of materials (BOMs). Why is this so important? Well, every improvement and maintenance task you undertake needs to go through the work order process, and having a reliable BOM makes that process much smoother.

To achieve accurate BOMs, you can take two approaches:

  • Data mine the equipment files – To extract valuable information to enhance or create precise BOMs. This involves digging deep into the data to uncover all the necessary components and their specifications.
  • Establish a continuous improvement process – Involves collaboration between technicians and the maintenance team. As technicians close work orders, they can identify any missing or incorrect components in the BOM. These discrepancies can then be promptly corrected and entered into the computerized maintenance management system (CMMS).

By ensuring accurate BOMs, you streamline your maintenance and improvement efforts. Technicians have access to the right information, enabling them to carry out tasks efficiently and effectively.

What Are Data Silos?

In many facilities, a common challenge arises: the existence of data silos. Over time, separate teams and departments naturally accumulate their own collections of data, creating isolated islands of information. It’s like each group has built its own fortress of data, evolving independently from one another.

The problem becomes apparent when you try to access and integrate predictive maintenance data from these silos. It can be a daunting task, like navigating a complex maze. However, wouldn’t it be wonderful if we could correlate and connect the valuable insights from one silo to another?

Breaking down these data silos is key to unlocking the full potential of your facility’s information resources. By bridging the gaps and fostering collaboration, you can achieve a more comprehensive and unified understanding of your operations. Imagine the power of correlating data across teams and departments, uncovering hidden patterns, and gaining deeper insights into your facility’s performance.

By implementing strategies and technologies that promote data sharing, collaboration, and interoperability, you can overcome the challenges posed by data silos. Embracing a holistic approach to data management allows you to harness the collective knowledge and expertise of your entire organization, leading to improved decision-making and enhanced operational efficiency. It’s time to break down those silo walls and connect the dots to unlock the full potential of your data-driven capabilities.

How to Know if You Have Data Silos

You might have a data silo if you find yourself:

  • Relying on scattered Excel spreadsheets
  • Struggling to retrieve data promptly
  • Dealing with random and selective software usage
  • Unable to find data illustrating a big-picture view of the business
  • With departments reporting inconsistent data and errors going uncorrected
  • Hearing complaints about a lack of data for specific business initiatives

Another clue is when your teams operate independently, almost like separate businesses, making it difficult to see the big picture. Inconsistent data and uncorrected errors further compound the problem, hindering collaboration between different areas. And, if someone tells you, “No, that’s my data. You can’t have it,” then we need to move beyond that mentality to stay competitive. Data silos slow us down, and we all know it.

Just think about the risks associated with working solely on Excel sheets. Spreadsheet nightmares like accidental deletions, formatting mishaps, and data jumbles can strike without warning, potentially ruining everything you’ve worked on in the blink of an eye.

The Danger of Data Silos: An Example

When it comes to inspecting equipment, we often find ourselves trapped in our own silos of expertise. Each operator looks at a pump and thinks, “Well, there’s one minor issue, but it’s not a big deal, so let’s give it a pass.” The lubrication technicians notice that the pump is dripping oil, yet they too decide to overlook it. Then, maintenance steps in and reviews the maintenance history, discovering that the pump needs repair every six months, but aside from that, everything seems fine. However, when we take a predictive approach and look at the high vibration on the inboard bearing, a different picture emerges.

From within each silo, the machine appears to be in acceptable condition. However, if we break down these silos and examine the situation as a whole, we start to realize that each group identifies its own set of problems. It becomes evident that this fragmented approach isn’t in our best interest.

By breaking down the barriers between silos and adopting a holistic perspective, we can effectively address the underlying issues that may not be apparent when we only consider individual viewpoints.

How to Eliminate Data Silos

We all know that things can be better, and the key is to eliminate those stifling data silos. Whether it’s at the corporate or enterprise level, the goal is to create a centralized data warehouse or data lake where we have a clear view of all our data. This allows us to query and analyze it without causing chaos.

By pulling together this unified data, we can uncover valuable correlations that propel us forward and drive improvement. Integration platforms as a service also come into play, particularly at the higher levels of the organization.

However, if you don’t have the same level of influence or resources, there’s still hope at the plant level. You can seek an all-in-one solution, a single platform that holds and presents most of the data, removing barriers and providing transparency. This platform becomes the hub from which you can easily create reports and dashboards.

At the facility level, obtaining funding for such a solution may be more achievable, as it falls within your decision-making rights. However, regardless of the approach, the crucial goal is to liberate information from its protected and proprietary silos, enabling everyone to access and leverage it. This shift can make a tremendous difference in your daily operations.

Imagine a world where issues are addressed promptly, allowing you to sleep better at night. Gone are the days of scrambling to fix problems on long weekends. By breaking down these silos, we pave the way for smoother operations and more efficient workflows.

Processes to Guide Decision Making

Once we have the necessary data, it’s crucial to employ processes to guide our decision-making. We should strive for data-driven decisions that follow established processes. By implementing processes, we can consistently make informed decisions and evaluate subjective data using a pass-fail approach. The goal is to encourage action in the desired direction, even if we don’t always achieve it immediately. We need to determine where we want to go and establish essential processes to facilitate our journey. Assuming you’ve already mapped your assets and identified critical aspects, here’s a quick list of processes you should have in place:

Planning and Scheduling Process

All improvement work, repairs, and replacements should go through a well-defined planning and scheduling process. If we struggle in this area, our productivity will be affected. Consider the timing of meetings, schedule distribution, planned work execution, outage management, and handling new requests. Additionally, make sure the weekly schedule is locked in and posted by noon on Friday for the following week. This allows everyone to know what they’ll be dealing with in the upcoming week.

Work Request Entry Process

Establish a process for entering complete and well-written work requests. Define how work requests are entered and ensure that work orders contain clear job steps.

FMEA Process for Assigning Equipment Criticalities

Develop a process that assigns equipment criticalities based on what’s best for the business, not just for individuals. By following consistent criteria, we align our efforts and avoid personal biases.

Inspection Processes

Define the inspection processes for different roles, such as lubrication technicians and operators. Determine how inspections are performed, including predictive inspections, and establish a feedback mechanism for those conducting inspections. Communication regarding the status of work orders or rejections, along with updates on resolved issues, is crucial.

Feedback Process

By implementing these processes, you ensure that important information is conveyed to the right people and that progress is acknowledged. It’s essential to address human nature, which often focuses on the next challenge, by actively communicating the resolution of past issues. This feedback process serves as a reminder that certain problems have been solved and eliminates lingering concerns.

In summary, implementing effective processes facilitates data-driven decision-making and fosters a cohesive approach. With clear guidelines and communication channels, we can tackle challenges more efficiently, ensuring progress and instilling confidence throughout the organization.

Final Steps of Data-Driven Inspections

Inspecting your operations is crucial, and the process should focus on identifying past failures that are likely to recur in the future. Pay attention to failures that may have low odds of happening but carry significant consequences, even if they seem unlikely. These areas warrant inspection.

However, it’s essential to strike a balance. You don’t want to get caught up in excessive inspections that hinder productivity. Eventually, you need to get back to running the plant or fixing things. So, it’s wise to identify the failures you want to inspect and determine how to handle them when they arise.

Avoid the trap of collecting excessive data just because it’s possible. Remember, the purpose of inspections is to identify and fix issues. Whether the problems stem from subjective or objective data, don’t fall into the pattern of inspecting something and confirming what you already know to be true. For example, if you already know an aging component is worn out, inspecting it during an outage only to fix it later is counterproductive.

Instead, utilize inspections as a driving force for improvement and action. Establish appropriate triggers and utilize feedback effectively. Often overlooked, the feedback process plays a vital role in motivating people to take the right actions when they witness changes happening. It truly makes a difference.

Consider implementing effective communication channels to share inspection results and progress. Create blog posts, include updates in newsletters, display results on facility TVs, and discuss findings during safety meetings. Breaking down silos and fostering collaboration will help us achieve our goals.

In summary, inspections should target potential failures based on past experiences and future probabilities, while avoiding excessive data collection. The focus should be on using inspections to drive improvement, supported by clear communication channels and a feedback process that motivates action.

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Data-Driven Machine Inspections & Results

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