Digital transformation continues to gain traction across numerous business sectors. In 2022, companies invested nearly $2 trillion in digital transformation technologies. By 2026, it is expected to reach $3.4 trillion. While digital transformation has been embraced for certain industrial segments - like rotating equipment - fixed equipment has been left behind.
Why are so many companies investing in Industry 4.0 technologies? When done right, it is lightning in a bottle. Improvements to safety, uptime, and throughput accelerate the winners to the front of the pack faster than ever.
The payoff from digital transformation can be significant, but the success rate is shockingly low. Forbes reported that the risk of digital transformation failure falls between 70% and 95%.
As you start your digital transformation journey, this blog will guide you through four steps to beat the odds and explain the critical element most strategies are missing.
What is Digital Transformation?
Before diving in, you may be wondering what we mean by a digital transformation strategy. It is the process of implementing digital technologies to modernize, evolve, and improve non-digital processes. You can think of these changes as technology-enabled optimizations.
When leveraged successfully, the right technologies will accelerate and improve operations in many aspects. Digital transformation technologies include digital twins, automation, the Internet of Things (IoT), augmented reality (AR), cloud computing, and artificial intelligence (AI).
However, some industries have taken longer to adopt these innovations. The methodologies commonly used to analyze critical infrastructure are resource intensive, unreliable, dangerous, and manual. With large industrial equipment, asset failures can cause devastating consequences for workers, communities, and the environment. Facilities must mitigate risks with accurate evaluation and maintenance plans.
The antiquated methods used to evaluate asset health leave significant opportunities for improvement through digital transformation. However, facilities need to optimize operations with the right approach, eliminating guesswork for confident next steps.
Step 1: Setting an Accurate Baseline with Full Health Scans
With traditional infrastructure inspection methods, an inspector will manually take readings on various points of an asset. This process results in insufficient information and gaps in coverage, capturing data that, in most instances, represents only 1-5% of the asset.
Additionally, the quality of the data captured is subjective to the experience and skill level of the inspector. Making confident decisions about your next steps may feel impossible when you only have a tiny sliver of information guiding your plans.
Therein lies the problem. Without using comprehensive data as the starting point, you may waste time and resources on plans that don’t solve the real problems.
Starting with a complete health scan is the most critical step in digital transformation. It provides a baseline for current asset health, which informs future decision making. However, most digital transformation strategies are missing this foundational element.
Companies need to leverage advanced inspection robots and AI-powered data analysis software to obtain a full health scan of assets. For example, Gecko’s wall-climbing robots collect 1,000x more information with continuous data capture at speeds significantly faster than traditional methods.
Facilities can have peace of mind that the full-coverage scan won’t have any blindspots, leaving no stone unturned. Then, the millions of data points feed into a software platform to translate the raw data into comprehensive maps, models, and digital twins.
Many companies fail to optimize long term because they invest in digital transformation and Industry 4.0 solutions before they even understand their problems. Once you have a complete analysis of asset health, then you can begin your digital transformation journey.
Step 2: Optimize Maintenance – Today and Tomorrow
Having a thorough picture of asset health can help optimize maintenance plans in both the short and long term. Facilities can analyze 3D map visualizations to hone in on problem areas that need addressed immediately. The full-coverage analysis informs where to deploy resources to proactively fix time-critical issues before equipment failures occur.
Secondly, the analysis helps create precision maintenance plans for the longer term. With traditional methods, facilities typically have a spreadsheet listing hundreds of assets at the plant. When you rely on incomplete, disparate information, it becomes nearly impossible to safely schedule maintenance and procure resources in a cost-effective and time-efficient manner before problems surface.
By digitizing this process, the software pulls together data layers to build priority lists based on an asset’s condition. Decision makers can refer to one source of truth with intuitive, easy-to-understand dashboards.
Going a step further, the software can integrate plant criticality lists to overlap with the full health scan data to ensure that the most critical assets are prioritized to maximize seamless productivity and safety simultaneously. This expands a facility’s scope from analyzing an individual asset to effectively managing an entire network of assets, gaining a holistic view to properly prioritize what needs to be repaired and when.
Accurate, deep data insights empower facilities to track down the root cause of issues, fix immediate problems before failures occur, and monitor how assets age over time. Decision makers can rest assured that the right maintenance activity is performed at the right time.
Step 3: Optimize CapEx
Data analysis software unlocks complete visibility into your problems and blind spots. With a comprehensive understanding of your entire network of assets and priority levels, you can confidently build predictive maintenance plans that optimize your capital expenditure (CapEx) budget.
Predictive maintenance plans help forecast when assets will need to be repaired to ensure issues are fixed before a failure occurs. This not only maximizes asset reliability and productivity but it will also minimize your costs. According to a U.S. Department of Energy report, a predictive maintenance program could achieve 30% to 40% savings.
The report also cited the following regarding the implementation of predictive maintenance programs:
- Return on investment: 10 times
- Reduction in maintenance costs: 25% to 30%
- Elimination of breakdowns: 70% to 75%
- Reduction in downtime: 35% to 45%
- Increase in production: 20% to 25%
Too often, companies waste time, money, and resources when there isn’t a clear picture of overall health. For example, suppose an inspector detects corrosion in an area of an asset. In that case, decision makers may plan to replace the unit, which would cost millions of dollars and cause extensive downtime. However, if that decision maker had access to the full health analysis, they would be able to confidently identify the precise locations where degradation is occurring to make targeted repairs that safely extend the life of the asset.
Using technologies like digital twins, companies can analyze “what if” scenarios to inform predictions. Within the software, the operator can toggle different variables, such as end of life dates, failure thresholds, and capital costs to optimize expenditures.
Data software simplifies decision making. By addressing problem areas proactively with advanced data analytics, you can safely extend the life of assets and your CapEx return on investment.
Step 4: Optimize Process
The final step is where things come to life in a big way. Now that you have the full-coverage analysis of your entire network and predictive maintenance plans, you can begin comparing assets to identify trends in the data.
Every asset is unique. Two tanks can be constructed on the same day, but they can age entirely differently. With full health scan data at your fingertips, you can quickly identify discrepancies between how the two assets are aging.
Several variables can affect the health and viability of an asset. After finding the hot spots, you can use operating process data to go even further. For example, a facility could layer data regarding flow rates, chemical makeup, valve positions, and weather conditions.
These data layers can help identify and benchmark the processes that operators should follow to extend asset life. Trends in the data can pinpoint root causes and help define standard operating procedures (SOPs) that optimize asset life cycles.
Your Success Begins with Data
Most companies fail with digital transformation because they skip ahead to start at Step 4. Without an accurate foundation of asset health, you are building strategies that are based on assumptions. Uninformed plans can result in investments, procedure changes, and SOPs that solve the wrong problems, wasting valuable resources.
Alternatively, data-led strategies start with an accurate baseline and drive measurable process improvements that yield real results. When leveraged correctly, data makes decisions effortless, confident, and effective.
For example, digital transformation technologies can be utilized to generate targeted repair plans for individual assets while also giving the ability to create maintenance prioritization lists for an entire network of assets. Decision makers can easily pinpoint when and where to deploy resources across their facilities in the near and long term. Knowing the whole picture with deep data insights will improve efficiency, productivity, and reliability now and in the future.
Discover how a company was able to save millions of dollars by taking a predictive maintenance approach for its aboveground storage tank by partnering with Gecko Robotics.
