In the world of manufacturing and industrial operations, a lot of confusion still swirls around TPM. Is it “Total Preventive Maintenance” or “Total Productive Maintenance”? Are they the same thing or different?
Let’s clear the air.
Total Preventive Maintenance (TPM) is focused on scheduling checks and interventions to reduce the chance of a failure. But Total Productive Maintenance (TPM) on the other hand is focused on more than just prevention, it’s a holistic maintenance transformation. It drives toward zero breakdowns and losses by involving everyone, not just the maintenance department.
In fact, you could argue that the bridge between the two isn’t just a process difference; it’s about intersecting and connecting people.
The TPM paradox and why we still get confused
For years, many organizations have used “TPM” to refer to Total Preventive Maintenance, focusing heavily on schedules, work orders, and checklists. While preventive maintenance is an essential part of operational efficiency, it often exists in a silo and is carried out by maintenance teams alone, detached from frontline operations.
Total Productive Maintenance, on the other hand, aims to maximize the effectiveness of equipment by eliminating all forms of loss, including downtime, speed losses, and defects.
This model, which has evolved into TPM 4.0 today, is inherently cross-functional. TPM 4.0 moves away from preventive maintenance and moves more towards predictive maintenance approaches. It brings maintenance out of the shadows and into the hands of everyone who touches the equipment, especially the people who know it best: your operators.
TPM isn’t just about managing machines. It’s about empowering the humans behind them.
A brief history of TPM and Nippondenso
In order to understand TPM we need to under the concept of productive maintenance, and where it came from. Productive maintenance originated in Japan in the early 1950s, and was influenced by Dr. W. Edwards Deming, who promoted the Shewhart cycle (plan-do-check-act).
In 1960, Nippondenso, a Toyota Group company, implemented a plant-wide preventive maintenance program for its automated processes. Initially, maintenance was handled solely by the maintenance department, but this change required a large number of specialized personnel.
To address this need, Nippondenso trained machine operators to perform routine maintenance themselves. This approach reduced labor costs, gave operators a deeper understanding of their equipment, and allowed them to detect problems early on. Maintenance teams were then free to focus on more complex repairs and long-term reliability improvements. The enhanced communication between operators and maintenance led to fewer breakdowns, better product quality, and reduced defects.
These practices evolved into a system combining preventive maintenance and maintainable improvement, then termed productive maintenance. Toyota became the first company to fully adopt and be certified in TPM, and Nippondenso received the distinguished plant prize from the Japanese Institute of Plant Engineers (JIPE) for its development and implementation of the methodology.
Traditional Preventive Maintenance and Total Productive Maintenance: How they work and connect
The flowchart contrasts Traditional Preventive Maintenance (PM) with Total Productive Maintenance (TPM), showing how each approach evolves and intersects at the operator level. On the left, Traditional PM is depicted as a top-down, schedule-driven process focused on minimizing downtime through planned interventions, often relying heavily on maintenance teams and sensor data.
On the right, TPM emphasizes a holistic, bottom-up strategy where operators play a central role in maintaining equipment, improving Overall Equipment Effectiveness (OEE), and fostering teamwork. The intersection highlights how empowering operators with tools, training, and ownership bridges the gap between reactive and proactive maintenance, driving continuous improvement and operational excellence.
The human element of prevention is more than a schedule
Traditional PM programs often live in the realm of planners, schedulers, and specialized techs. And while that structure keeps critical equipment running, it can also isolate maintenance knowledge from day-to-day operations.
True “Total” Preventive Maintenance demands the involvement of everyone. That’s where Autonomous Maintenance (Jishu Hozen) comes in, it’s a core pillar of TPM that enables machine operators to take ownership of routine care like cleaning, lubrication, and basic inspections.
Operators are the front lines of failure detection. They hear strange noises before they’re detectable by sensors, feel vibrations that indicate imbalance, and spot oil leaks or misalignments while doing their daily rounds. Their involvement turns routine tasks into your most valuable early warning system. By empowering your people to engage with maintenance proactively, you’re turning preventive action into productive excellence.
From prevention to productivity: The unseen ROI
Bridging the gap between prevention and productivity isn’t a theory; it’s measurable. There are six main preventable losses in maintenance:
Breakdowns: Equipment failures that halt production, often caused by overlooked wear, poor lubrication, or delayed minor repairs.
Setup and adjustments: Time lost during changeovers or fine-tuning due to unclear procedures, poor training, or inconsistent standards.
Idling: Periods when machines are ready but not running, often due to poor coordination, missing materials, or unclear responsibilities.
Minor stoppages: Frequent short interruptions from issues like jams, misfeeds, or sensor faults that are often ignored but add up over time.
Quality and rework: Defects and reprocessing caused by equipment not running at optimal condition, leading to wasted time and materials.
Operator-led preventive care empowers frontline maintenance workers to take ownership of basic maintenance tasks like cleaning, inspecting, and tightening. This helps catch early signs of wear or malfunction before they become costly breakdowns. This proactive involvement builds a culture of shared responsibility and continuous improvement, aligning with the principles of Total Productive Maintenance (TPM). When operators are trained and engaged in equipment care, it reduces reliance on reactive maintenance, enhances equipment reliability, and drives productivity gains.
Here’s how operator-led preventive care feeds into true Total Productive Maintenance (TPM) outcomes with examples:
Outcome
Example
Reduced minor stops and slowdowns
Small hiccups are caught before they snowball into unplanned downtime.
Faster problem solving
Operators who know their equipment inside out can troubleshoot issues quickly and communicate them clearly
Increased morale and ownership across the maintenance team
When people feel responsible for the health of their machines, they take pride in their performance.
Empowered teams constantly find ways to improve equipment reliability, safety, and ease of maintenance.
Safer work environments
Well-maintained machines reduce injury risks, especially when operators are trained to notice unsafe conditions early.
There’s even more ROI to be found beyond this, for example you would see:
Reduced emergency repair costs through fewer breakdowns.
Lower production losses thanks to minimized scrap and rework.
Optimized spare parts inventory, avoiding overstock and stockouts.
Extended asset lifespan, deferring expensive capital purchases.
Lower energy consumption as machines run cleaner and more efficiently.
Building a financially intelligent TPM strategy
To make Total Productive Maintenance (TPM) stick and to secure buy-in from leadership, it needs to be tied to business goals. Here are the steps on how to build a TPM strategy with financial intelligence:
Align with business objectives:Maintenance should support revenue, profit margins, and delivery performance, not just uptime.
Use data to guide decision making:CMMS and EAM systems can reveal trends in equipment failure, maintenance spend, and recurring issues that training or design changes could resolve.
Invest in people and technology: Justify training, technology upgrades, or predictive analytics tools by linking them to clear business impacts.
Design for simplicity: A TPM strategy only works when it’s understood by everyone, so design processes are easy to adopt on the shop floor.
Summary: Where predictive meets productive
The future of maintenance isn’t one model versus another. It’s convergence. Total Predictive Maintenance gave us the sensors, scheduling tools, and early detection methods to reduce unplanned downtime. Total Productive Maintenance, specifically TPM 4.0, gives us the culture, structure, and cross-functional empowerment to make those tools stick and to scale performance across the whole operation.
The 10th annual State of Smart Manufacturing Report from Rockwell Automation recently dropped, and one thing is clear: Artificial intelligence (AI) isn’t the future—it’s the present. Manufacturers are doubling down on digital transformation (DX), and smart maintenance is front and center.
From quality control to cybersecurity, manufacturers are turning to AI and SaaS tools (like a CMMS(opens in new tab)) to help navigate uncertainty, close skills gaps, and build operational resilience. In this blog, we’ll cover what maintenance professionals need to know from the report and how Fiix CMMS is helping teams get ahead.
Smart manufacturing is here to stay and will continue to grow
According to Rockwell Automation’s global survey of 1,560 manufacturing leaders:
95% have invested in or plan to invest in AI/ML, GenAI or Causal AI within five years.
41% are introducing AI and automation to address labor shortages and skills gaps.
50% plan to use AI/ML for quality control this year.
Yet, for all of this vested interest in AI tools, only 44% of collected data is used effectively, showing room to improve how we operationalize insights.
Smart manufacturing is no longer optional. With labor and quality pressures on the rise, tools like Fiix Asset Risk Predictor and Fiix Foresight analytics engine help manufacturers turn underused data into actionable intelligence—fast.
The report also highlights five top use cases for AI and machine learning (ML) in 2025:
Quality control (50%)
Cybersecurity (49%)
Process optimization (42%)
Robotics (37%)
Logistics (36%)
Each of these directly impacts how maintenance is planned, scheduled, and executed. The good news is that AI-powered CMMS tools can help flag anomalies, prevent downtime, optimize resources, and protect plant-floor systems. Fiix CMMS for example, helps maintenance planning by surfacing inefficiencies and organizing team workflows and assets.
Tools like Fiix Foresight leverage AI to track equipment failure patterns, suggest optimizations, predict stockouts, and boost asset reliability—all without complex configurations or data science teams.
Smart maintenance still needs smart people
Despite all the AI excitement, Rockwell Automation’s report reveals a critical truth: technology doesn’t replace people—it empowers them.
83% say analytical thinking, communication, and teamwork are top skills when hiring.
Nearly half of manufacturers plan to repurpose or hire more workers in response to digital transformation.
AI upskilling jumped 10% year over year as a critical organizational capability.
Don’t forget: AI removes tedious, manual day-to-day tasks, surfaces useful insights anyone can act on, and expands workers’ capacity to focus on higher-value work, helping them achieve their goals.
Fiix CMMS focuses on user-friendly AI for fast onboarding. With templates, training tools(opens in new tab), and no-code customization, maintenance teams can adopt AI without the steep learning curve.
Cybersecurity is a growing concern
Cybersecurity rose to become the #2 external risk in 2025. The integration of connected systems (IT/OT) and smart devices increases exposure and therefore, increases the importance of AI for threat detection and prevention.
38% are already using operational data for cybersecurity protection.
Ransomware attacks in manufacturing are 3x higher than in other industries.
Fiix CMMS in action
As a cloud-based software, Fiix CMMS adds layers of protection through secure data hosting, top security certifications, permission controls, and integrations that align with your IT/OT architecture.
Data is everywhere we look, but it still needs context
One of the most telling stats from this year’s report? Less than half of the data collected by manufacturers is used effectively. The gap between collection and action can cost manufacturers lost insights, reactive repairs, and inefficient processes.
Fiix CMMS in action
With real-time dashboards, custom reports, and API integrations, Fiix CMMS helps you capture, contextualize, and act on your data.
In summary, maintenance remains at the heart of smart manufacturing
Rockwell Automation’s 2025 report highlights a global push toward smarter, faster, and more resilient operations. But it’s the intersection of technology and people, like AI-enhanced maintenance teams, that will define true success.
With Fiix CMMS, you’re not just adopting technology. You’re building a maintenance program that is:
In recent years manufacturers and by extension, maintenance teams, have faced a series of challenges from pandemics, supply chain slowdowns, and now a demand for skills in the workforce that are difficult to come by. At the same time Industry 4.0 technologies(opens in new tab)—such as automation, IoT, AI, and advanced robotics(opens in new tab) have streamlined many production processes, and the demand for skilled workers who can operate, maintain, and optimize these systems has subsequently increased.
It’s become clear that there’s a widening gap in skills for manufacturers aiming to remain competitive. But without a workforce that’s knowledgeable in digital tools and systems, operational efficiency, productivity, and overall equipment effectiveness (OEE)(opens in new tab) are at risk.
In this blog we will address the current skills gap facing manufacturers and maintenance teams and provide solutions to upskill the current workforce, and strategies to address skill gap challenges.
What is the skills gap and why has it become critical?
The skills gap refers to the issue surrounding current labor markets where finding workers who have the manual, operational, and technical skills necessary to work in manufacturing and by extension, maintenance has become tiresome and difficult. According to our State of Smart Manufacturing (2024)(opens in new tab) report, attracting new employees with desired skillsets has become the number one obstacle manufacturers are facing in terms of their growth. Additionally, in the previous year’s report (2023), 84% of respondents identified employee retention as their top obstacle. This data tells us that not only has the demand for skilled workers increased, so has the desire to retain these workers.
The skills gap has then slowly creeped up to becoming a big concern as of late. Some of the key reasons why are:
Rapid technological advancements: Industry 4.0 has introduced things like automation, artificial intelligence (AI), Internet of Things (IoT), and predictive maintenance (PdM). These things require a workforce that’s knowledgeable in data analytics, machine learning (ML), and machine operation. Many workers, however, lack the skills to manage and maintain these systems.
An aging workforce: A big portion of the manufacturing and by extension maintenance workforce is nearing retirement. As these skilled workers leave, there’s a shortage of younger workers to fill their roles.
Lack of necessary training and documentation: Without proper training programs and up-to-date documentation, current employees cannot effectively operate and maintain advanced systems. There’s also the challenge of little to no team members available to train new employees who are onboarding.
Declining interest in trades and technical education: There’s been a societal shift that emphasizes college and university degrees over vocational training and technical careers. As a result, fewer young people are pursuing the skills needed for manufacturing and maintenance roles.
As these challenges merge, the skills gap becomes an important factor in the disruption of daily operations. It also jeopardizes long-term competitiveness in a changing industrial landscape, and also causes a productivity decrease and safety risk.
“The challenges teams are facing today in terms of skills gap causes a lot of disruption. For one thing, there’s a decline in productivity that’s a result of limited knowledge and expertise, then there’s the inability to use any new technologies since workers aren’t trained or skilled in them,” says Jason Afara, our Director of Solutions Consultants. He adds: “There’s also safety considerations, like the improper use of machines and equipment, failure to follow safety protocols, risk of equipment failure…all of these things tie back to the skills gap.” A final point Jason highlights is that the skills gap also puts additional strain on your best team members, since the team is often going to them to do more.
With so many risks to consider, what can teams do to mitigate and manage the challenges quickly?
“Well, the good news is there’s lots of ways to manage the skills gap, and we’re in the age of AI. Teams can start using AI to track data, retain knowledge, and manage processes,” says Jason. He adds: “We already do this on our CMMS for maintenance teams and have a knowledge repository for assets so that things don’t get lost if a skilled worker leaves or isn’t available.”
Jasons points present an interesting solution for manufacturers and maintenance teams to consider when addressing the skills gap. Leveraging technology like AI has grown in popularity, in fact, according to our State of Smart Manufacturing (2024) report, manufacturers believe that GenAI or casual AI is the #1 technology to address workforce challenges. Additionally, 83% of respondents anticipate using GenAI, making it the #1 on the list of technological investments for 2024.
Aside from leveraging AI, there are many different solutions to upskill the current workforce, one of the most obvious is for organizations to invest in training and development. This can take many different forms but the best steps to follow are:
Emphasizing the importance of continuous education and training for existing employees by having mandatory course credit requirements per year.
Investing in training programs like on-the-job training, online courses, and certifications.
Incentivizing managers and people leaders to foster a culture of education and upskilling. This can take the form of financial incentives (i.e., bonuses).
Tip for teams having trouble finding time to train their staff: You likely can’t take the entire team off the floor, but you could set aside some time to train team members once a week to ensure there is proper coverage on the floor.
Additionally, there’s also leveraging technology for upskilling. Employers can have their teams use e-learning platforms and virtual reality (VR) for practical training. There are even companies that offer VR training and specific authorized training centers, which is something companies can utilize to be most cost effective. Organization can also partner with educational institutions, this can include:
Partnering with local colleges, universities and trade schools to create tailored training programs.
Developing apprenticeship and co-op programs as pathways to development.
Using technology and automation to address the skills gap
Beyond just educational solutions, teams can also use automation and technology to help narrow the gap in the workforce. But integrating automation is a supplement, not a replacement for skilled workers. That being said, automation can bridge the gap over time by taking on routine tasks that don’t require a high-level of experience or expertise.
As Jason explains, “automation can cut the pressure on the business and teams who are lacking skilled workers… for example, technicians can use technology like a CMMS or specialized machine operations to help with automated and human tasks.” Let’s clarify what’s automated versus human tasks with some examples:
Automated tasks: Routine inspections, data collection, inventory management, and certain aspects of production processes like welding or assembly can be fully automated. These processes can be performed with greater speed and accuracy by machines, reducing the need for a large workforce in these roles.
Human-centric tasks: On the other hand, tasks that require critical thinking, creativity, and decision-making, such as diagnosing machine malfunctions, developing new production processes, or maintaining human-machine collaboration, remain reliant on human expertise. Human workers are essential in overseeing operations, managing automated systems, and troubleshooting when machines encounter unforeseen problems.
The good news is that by leveraging automation and technology, organizations can optimize their operations without sacrificing human touch. Additionally, people can work on more creative problem solving versus routine laborious tasks.
Human-machine collaboration and the skills gap
The role of workers will shift from performing manual tasks to managing, monitoring, and optimizing the performance of automated systems. Human-machine collaboration will allow for greater efficiency and productivity, but it requires a shift in mindset and skill set. Workers need to be equipped with the technical know-how to operate and collaborate with these advanced systems.
“To make the shift successful and less painful, companies got to invest in training and upskilling their workforce,” says Jason. According to him training should focus on three core areas:
Technical proficiency: Employees need to learn how to operate, maintain, and troubleshoot the automation tools and systems in place. This may include training in data analysis, machine learning, or how to use predictive maintenance software.
Soft skills: Workers must also develop skills in communication, teamwork, and problem-solving to collaborate effectively within a tech-enabled environment.
Succession planning: Managers should lead crossover meetings and have open communication with their employees to foster a positive culture.
Many forward-thinking companies have already embraced human-machine collaboration with impressive results. For instance, Fiat Chrysler Automobiles introduced collaborative robots—known as cobots—to work alongside their human employees on the production line. Cobots handle repetitive and physically demanding tasks, while human workers focus on quality control and problem-solving, creating a balanced workflow that leverages the strengths of both. This example demonstrates how a business can close the skills gap by embracing automation, not as a replacement for human workers but as a complement that enhances their capabilities.
Closing the skills gap will lead to more efficient operations
Addressing the skills gap in the manufacturing and maintenance sectors is crucial for the industry’s growth and resilience. By upskilling the current workforce and attracting new talent, businesses can bridge this divide and position themselves for long-term success. Industry leaders must take proactive steps in workforce development—whether through internal training, partnerships with educational institutions, or collaborations with recruitment.
Artificial intelligence (AI) and chatbots are nothing particularly new to the maintenance sector. Most sectors have begun using chatbots as part of their overall business operations. We have recently developed a similar innovation, the Fiix Maintenance Copilot, a Gen-AI-powered chatbot designed to resolve asset issues faster with instant answers to your maintenance questions. In this blog, we’ll review Fiix Maintenance Copilot and how it fits into our other product lines. We’ll also discuss the other ways that chatbots are making their way into maintenance and manufacturing.
What is Fiix Maintenance Copilot?
Managing day-to-day activities for maintenance teams can be complex and time-consuming. However, Fiix Maintenance Copilot(opens in new tab) is here to simplify and enhance the maintenance process by capturing your maintenance knowledge in one place, surfacing answers to your maintenance problems faster, and being a conversational and convenient operator for every maintenance team. It works like other chatbot experiences in that it’s a window that pops up a chat-style expertise for team members to ask questions regarding an Fiix Asset Risk Predictor (ARP)(opens in new tab) enabled asset. The information from the asset is stored in a knowledge base for the team to retain.
Fiix Maintenance Copilot can quickly answer questions about your ARP-enabled assets without having to manually review all of your data and documentation. This brings me to my next point: reviewing Fiix ARP and how it fits into the bigger picture of your maintenance.
What is Fiix ARP and how does Fiix Maintenance Copilot fit into it?
According to Mohammad Esmalifalak, Lead Data Scientist at Fiix, ARP, Fiix Prescriptive Maintenance(opens in new tab), and Fiix Maintenance Copilot should be distinct from three separate products, but one. “Fiix ARP detects anomaly operations, and then Fiix Prescriptive Maintenance prescribes solutions to help resolve the issues and prevent potential failures; our latest addition to this product line is Fiix Maintenance Copilot. They work together, not separately,” says Mohammad. He added that the Fiix Maintenance Copilot solves some of the common challenges that maintenance teams face when quickly finding information on an asset. Some benefits of Fiix Maintenance Copilot are:
Time-saving: It streamlines maintenance processes by providing quick access to information, interactive troubleshooting, and around-the-clock support. This can reduce downtime and increase productivity.
Accessibility: It offers support to technicians anytime, anywhere, 24/7, giving teams flexibility in their work environments.
User-friendly: The chatbot functionality makes it easy to interact with and answer questions, and it can access accumulated knowledge about maintenance procedures for the most critical assets.
Adaptability: The chatbot gets better over time and has machine learning (ML) capabilities, which lets it learn from user interactions and adapt responses over time.
“With this, product maintenance teams can get quick access to information versus searching and digging through the computerized maintenance management system (CMMS). It’s easy to use, and it gets better over time. The chatbot is equipped with machine learning capabilities, so it learns from user interactions and adapts,” says Mohammad. But if the product is learning and adapting, how do we keep data and information safe?
“An important question we often get is about customer safety with chatbots. For one thing, we’re not using an open-source platform for our chatbot, and like all Rockwell Automation platforms and products, our customer data and safety are there. We make sure that we don’t use any customer information for training any AI models that are open access or live outside the Rockwell secured instances as an extra measure of safety,” Mohammad added.
Fiix Maintenance Copilot’s versatility and adaptability make it a robust solution for maintenance teams looking to improve their operations.
How are chatbots benefiting maintenance teams?
Since chatbots are growing in popularity, many teams have begun using them internally and externally to manage their clients or partners. Internally in the manufacturing sector, teams often use chatbots to help with real-time troubleshooting and support, predictive maintenance, enhanced communication, and even sharing data-driven insights. Let’s review how some of these features are used in maintenance and manufacturing with examples:
Real-time troubleshooting and support: When machinery malfunctions, every minute of downtime translates into lost productivity and revenue. Chatbots provide real-time support by:
Offering diagnostic assistance: Analyzing symptoms and providing potential causes and solutions based on historical data and industry best practices.
Accessing knowledge base: Quickly retrieving information from manuals, past maintenance records, and technical documentation to assist technicians on the spot.
Guiding repairs: Providing a step-by-step for common repair procedures, ensuring that even less experienced technicians can perform tasks correctly.
Predictive maintenance: Preventing unexpected equipment failures can save teams time and costs, chatbots play a role by:
Analyzing data: Using machine learning (ML) algorithms to analyze data from sensors and other sources to predict when a machine is operating abnormally and is likely to fail.
Scheduling proactive maintenance: Recommending and scheduling maintenance activities before a failure occurs, reducing unplanned downtimes.
Optimizing maintenance schedules: Balancing maintenance activities to minimize disruptions to the manufacturing process while ensuring equipment reliability.
Enhanced communication and collaboration: Effective communication helps maintenance teams organize their day-to-day routines and tasks. Chatbots enhance this by:
Centralizing information: Providing a single platform for sharing updates, reporting issues, and tracking the status of maintenance activities.
Sending notifications: Alerting team members about upcoming maintenance tasks, critical issues, and status changes in real-time.
Facilitating collaborations: Enabling technicians to easily share insights, ask for help, and collaborate on complex issues through the chatbot interface.
Data-driven insights: Data is a powerful tool for improving maintenance strategies. Chatbots help in leveraging this data by:
Generating reports: Creating detailed reports on equipment performance, maintenance activities, and failure trends.
Analyzing trends: Identifying patterns and recurring issues to inform proactive maintenance strategies.
Providing recommendations: Offering actionable insights to optimize maintenance schedules, improve equipment reliability, and reduce costs.
Although Fiix Maintenance Copilot isn’t quite at the level of the above examples yet, it may still be a potential future for the product. “We’re just in the first stage of what’s possible with chatbots like ours. Right now, we’re just accessing from an internal knowledge base, but what happens if we go outside to something like Google? Now we’re expanding our knowledge reach, but we’d need to do so in a smart and safe way,” says Mohammad.
There’s so much potential for chatbots in the maintenance space, Fiix Maintenance Copilot is just one example,” Mohammad added.
By automating routine tasks, providing real-time support, enabling predictive maintenance, enhancing communication, and delivering data-driven insights, chatbots are becoming indispensable tools for maintenance teams.
Fiix Maintenance Copilot is designed to streamline maintenance teams’ tasks
With the number of tasks maintenance teams need to organize and keep track of new tools like chatbots can help teams keep up with the demands of their operations. Fiix Maintenance Copilot is a powerful Gen-AI-driven chatbot that offers a range of features to help teams access their knowledge base easily and quickly, ultimately saving them a lot of time and being a tool, they can lean on 24/7.
What can maintenance teams do to help meet the biggest business challenges of 2024? The impact of maintenance goes far beyond just downtime, so let’s dive into the results of Rockwell Automation’s 9th annual State of Smart Manufacturing Report (SoSM) to uncover the top obstacles facing manufacturers, how maintenance teams can help, and the useful technology investments delivering results.
The State of Smart Manufacturing
If you had to summarize this year’s SoSM report in one word, it might be “optimistic.” While the challenges facing manufactures are real, so are the potential solutions. In the face of economic headwinds, labor shortages, skills gaps, and cybersecurity concerns, decision-makers are turning to advanced industrial operations technology like AI to meet their concerns (SoSM, pg. 5). But before we get to the solutions, let’s breakdown the report’s top challenges to manufacturing growth in 2024.
By automating data analysis to generate predictive and prescriptive actions, industrial organizations can realize efficiency gains and overcome key challenges. – Sandy D’Souza, Fiix Product Expert
The Top Obstacles to Growth in 2024
As in previous years, this year’s SoSM report distinguishes between external and internal obstacles to growth.
Top 5 External Obstacles to Growth
Inflation
Rising energy costs
Cybersecurity risks
Shortages of skilled workers
Supply chain disruption
Unsurprisingly, rising inflation and energy prices topped the list as global events and supply-demand mismatches continue to impact companies in all sectors. In fact, inflation tops the list of external obstacles for the second year running. These pressures hit manufacturers particularly hard because they depend on physical inputs and often run comparatively energy-intensive operations.
Interestingly, the emergence of cybersecurity risks in the number three spot speaks to the double-edged nature of technological progress: As manufacturers invest in the interconnectivity between the physical and digital worlds through OT and IT technology, this progress has also brought with it novel security concerns.
Finally, skilled worker shortages and supply chain disruption continue to dampen growth, although there are some encouraging signs on the horizon that the supply chain issues may be finally coming to an end.
Topping this year’s list of internal growth obstacles, the global skilled labor shortage rears its head once again, with respondents agreeing on the difficulty of attracting new talent. Related to this, the challenge of deploying new technologies took the number two spot, with the difficulties compounded by the skills shortage.
Budget constraints and the endless tug-of-war between quality and growth took the number three and four spots, respectively, reflecting perennial business concerns.
Finally, the challenge of collecting and interpreting data for improvement was revealed to be widespread, capturing the number five spot.
How Maintenance Teams Can Help
Maintenance teams have a unique role to play in addressing these obstacles to growth. Far from being a silo or cost center, maintenance is in fact uniquely poised to help manufacturers rise to their challenges.
Here are the top ten ways maintenance teams can help meet both the external and internal challenges to growth we explored above.
External Obstacles
Inflation: Control maintenance costs by optimizing equipment performance, minimizing downtime, and extending asset lifespan, thus mitigating the impact of inflation on operational expenses.
Rising energy costs: By implementing preventive maintenance schedules and energy-saving strategies, teams can reduce equipment inefficiencies and energy waste, resulting in lower energy consumption and cost savings over time.
Cybersecurity risks: A high-quality CMMS offers robust security features and data encryption protocols to protect sensitive maintenance data from cyber threats, ensuring the integrity and confidentiality of critical information within the system.
Shortage of skilled workers: Enhance workforce productivity by providing intuitive tools and resources for maintenance teams, enabling them to work more efficiently and autonomously, thus mitigating the impact of skilled labor shortages on maintenance operations.
Supply chain disruption: Minimize the impact of supply chain disruptions by optimizing spare parts inventory management, identifying alternative suppliers, and implementing contingency maintenance plans to ensure equipment uptime and operational continuity during disruptions.
Maintenance impacts all three components of OEE – Availability, Performance and Quality. With modern technologies, maintenance teams can proactively identify the early warning signs of issues that can negatively impact OEE and thereby improve profitability. – Sandy D’Souza, Fiix Product Expert
Internal Obstacles
Attracting new employees with desired skillsets: Enhance workforce attraction by adopting modern, cloud-based, and user-friendly technologies that help improve productivity and organization. Its intuitive interface and advanced features attract skilled workers looking for simple solutions to help with everyday tasks and decision making.
Deploying and integrating new technology: Simplify the deployment and integration of new technology by seeking solutions that offer seamless compatibility with existing systems through easy-to-use APIs, ensuring smooth implementation and minimal disruption to operations.
Internal budget constraints: Understand the ROI of operational tools like a CMMS, which offers transparent pricing models and flexible subscription options, which allows organizations to align their maintenance software investment with budget constraints without compromising on functionality or performance.
Balancing quality and growth: Balance quality and growth by optimizing the maintenance processes that reduce downtime and improve asset reliability, thereby enabling manufacturers to meet increasing production demands without sacrificing product quality or customer satisfaction.
Capturing and contextualizing data to improve: Use a CMMS to take advantage of advanced data analytics and reporting capabilities, allowing your organization to capture, analyze, and contextualize maintenance data to identify trends, optimize performance, and drive continuous improvement across their operations.
How Manufacturers Are Responding
Meanwhile, prompted by these internal and external pressures, manufacturers are stepping up technology investment to counter risks and meet their growth obstacles head-on. In fact, technology investment in manufacturing is up 30% year-over-year (SoSM, pg. 9)!
To meet 2024’s unique challenges, manufacturers are rallying behind Cloud/SaaS and GenAI solutions, voting them in as the first- and second-best choices for return on investment. More general AI/ML solutions also make the list, coming in at number four. And in fact, AI/ML were also selected as delivering bigger business outcomes than any other capability in 2024 (pg. 10)! Essentially what we’re seeing is companies using Cloud and AI technologies as a lever to offset the pressure of multiple external obstacles.
Generative artificial intelligence (GenAI) rocketed up the technology priority list over the last twelve months, creating fierce demand for industrial applications embedded with this transformative technology – SoSM, pg. 4
Manufacturers and their maintenance teams can take advantage of these new technologies to overcome business obstacles by adopting a cloud-based, AI-powered CMMS solution like Fiix CMMS. Without a doubt, a CMMS like Fiix can exert a positive influence on every single one of the 10 internal and external business growth obstacles discussed above, digitizing existing process while unlocking entirely new ways of using your maintenance data to make decisions. But don’t take our word for it: Try Fiix for free today!
Paired with a data-driven culture, a modern CMMS can help establish corporate standards, set KPIs, and most importantly, measure operational performance and improvements over time. – Sandy D’Souza, Fiix Product Expert
About the SoSM Report
The State of Smart Manufacturing Report is an industry benchmark report detailing how manufacturers, OEMs, EPCs, SIs, and others are using and planning for technology in response to the challenges and opportunities they’re facing. The quality of any survey depends on a representative sample, and by drawing upon a large base of global industrial expertise, Rockwell Automation has made the 9th annual State of Smart Manufacturing Report their largest to date. Here are some key facts about this year’s report:
1,567 decision-makers in manufacturing participated in the survey
17 of the world’s top manufacturing countries were represented
64% of respondents work for firms with >$1B in revenue
The top industries surveyed were electronics/semiconductors, automotive, metals, and CPG
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