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Human Performance and Limitations 

Human performance and its limitations significantly influence maintenance outcomes, yet this aspect is frequently neglected in maintenance strategies. Cognitive factors, skill differences, and physical constraints can affect the accuracy and speed of diagnosing and repairing equipment failures.


When employees depart, it's not just a personnel change but a potential loss of invaluable knowledge and experience. Veterans of the workplace often possess irreplaceable insights into machinery nuances, troubleshooting techniques, and operational efficiencies, honed from years of hands-on experience.

In response to this challenge, digital work instructions and simulations have emerged as innovative solutions to bridge the skills gap. Unlike traditional manuals or training programs, these digital tools provide interactive, engaging experiences that effectively encapsulate the tacit knowledge of experienced workers.

The creation of digital work instructions and simulations is a meticulous process. It involves distilling expert knowledge into formats that are accessible, understandable, and actionable. This includes capturing the rationale behind each step, highlighting potential pitfalls, and sharing the tips and tricks that come with years of practice.

Developing these digital knowledge bases serves multiple purposes. Firstly, it helps mitigate the risk of knowledge loss due to employee turnover. Secondly, it speeds up the training and upskilling of newcomers, making them productive faster and with a better grasp of their roles. Lastly, it fosters a culture of continuous improvement and learning, treating knowledge as a dynamic, evolving asset.

The benefits of digital work instructions and simulations extend well beyond mere knowledge preservation; they are fundamental to building a workforce that is prepared for the future. By making complex knowledge more digestible and engaging, they simplify the understanding of intricate systems and processes.

The shift towards capturing and sharing knowledge digitally is a strategic move for industries aiming to manage and leverage their collective expertise more effectively. It safeguards against the loss of critical operational knowledge and empowers future employees with a rich, accessible learning environment. Thus, the departure of seasoned employees no longer creates a vacuum but leaves behind a well-curated knowledge repository, ready to guide the next generation of industry professionals

Human factors and limitations


In the realm of maintenance, the human element significantly impacts the precision, speed, and capability to avert machine failures. Factors like cognitive load, variability in skills, decision-making under duress, and physical stamina play into this. A technician's efficacy in identifying and addressing issues is not solely reliant on their expertise and tools but is also heavily influenced by their mental and physical wellbeing, which can be compromised by fatigue, stress, and their working conditions.

Cognitive biases and the use of heuristic shortcuts, while sometimes beneficial, can lead to inaccuracies in diagnostics, particularly with complex systems where signs may indicate multiple potential issues. The pressure to quickly return to operational status can often result in the selection of temporary fixes over more sustainable solutions.

Digital innovations, such as realistic simulations, digital workflows, and tablet-based instructions, offer a powerful countermeasure to these challenges. Simulations allow for immersive, machine-specific training that equips technicians with a safe space to develop and refine their skills, reducing the likelihood of errors in real-life situations. Digital workflows enhance organizational efficiency, automating routine tasks and ensuring that maintenance activities are conducted methodically and collaboratively. Meanwhile, tablet-based instructions provide immediate, easy-to-follow guidance, lightening the cognitive load on technicians and aiding in the accurate completion of tasks, even in high-pressure scenarios.

By embracing these digital tools, organizations can significantly mitigate the effects of human error. This approach not only increases maintenance reliability and availability but also cultivates a workforce that is more adaptable, skilled, and prepared to tackle the complexities of modern industrial environments.

Human factors and limitations
Large mining machine - reduce downtime


Misdiagnosis and the presence of inexperienced workers in the maintenance team can significantly increase repair times and, by extension, total downtime costs. These issues not only extend the time required to correctly identify and fix problems but also contribute to unnecessary expenditures on incorrect parts, wasted labor, and, most critically, lost production time.

The Impact of Misdiagnosis
Misdiagnosis occurs when the actual root cause of an equipment failure is incorrectly identified. This could lead to several negative outcomes:

  • Time Wastage: Precious time is lost in attempting repairs that do not address the real issue, thereby extending the equipment's downtime.

  • Increased Costs: Resources are expended on unnecessary parts and labor. For high-value equipment, these costs can escalate quickly.

  • Extended Downtime: Every additional hour that equipment remains non-operational directly affects production volumes and can lead to missed deadlines, affecting customer satisfaction and potentially leading to contractual penalties.

The Role of Inexperience
Inexperienced workers may lack the nuanced understanding of equipment that comes from years of hands-on experience. This lack of experience can lead to slower diagnosis times, less efficient repair strategies, and a higher probability of misdiagnosis. Training and mentorship programs can mitigate these issues, but they require time and investment.  Digital solutions are much easier and faster to deploy 

The Significant Impact of Marginal Decreases in machine downtime
Even a marginal decrease in downtime can have a disproportionate effect on downtime costs. Consider a 24/7 mining operation with a high dependency on continuous machinery operation. A reduction in downtime from 4 hours to 3.5 hours, for instance, represents a 12.5% improvement in repair times. For equipment whose downtime costs are measured in tens of thousands per hour, this reduction can result in substantial savings.

Moreover, reducing equi,emt downtime improves overall equipment availability, leading to higher productivity and better utilization of assets. This increased efficiency directly contributes to the bottom line, enhancing profitability.

Calculating the Cost Impact
The financial impact of improved downtime can be calculated by considering the cost of downtime per hour and multiplying it by the reduction in downtime achieved through improved maintenance practices. For example, if the downtime cost for a piece of equipment is $10,000 per hour, reducing the downtime by just 0.5 hours saves $5,000 per incident. Over a year, multiple incidents can lead to significant savings.

Addressing the challenges posed by misdiagnosis and inexperienced workers is crucial for minimizing downtime and reducing overall produciton and maintenance costs. Investments in advacned training, digital diagnostic tools, and predictive maintenance technologies can significantly improve maintenance efficiency. Even small improvements in downtime can lead to large financial benefits, underscoring the value of focusing on maintenance practices and personnel training as strategic business investments.


Mining, metals and other heavy-industrial companies lose 23 hours per month of production time per machine.  read more

  1. Application Developement Costs*:  To assist you in filling out this piece of information consider incorporating other costs associated with average APP development* or reach out to us here for a detailed discussion.

  2. Downtime Cost Per Hour:  Site specific downtime cost per hour.  Can be single machines or overall site downtime cost.  

  3. Downtime Hours Per Month:  Site specific downtime hours per month.  Can be single machines or overall site downtime hours.  We recommend single machine groups.  This allows ultra focus on very specific machine costs for individualised solutions and tracking of downtime before and after

  4. Estimated Downtime Reduction (%):  Enter a reduction in downtime you would like to see per incident in hours.  Be realistic

  5. Calculate the ROI: Once you've inputted all the necessary information, hit the 'Calculate' button.  This figure represents the return on your investment relative to its cost, giving you a clear picture of its financial viability.

 *Average App developments range from 50k - 100k and upwards.  More info here

How to...

Its Calculated 

Our newly implemented ROI (Return on Investment) calculator is designed to simplify and demystify the financial benefits of investing in specific projects or technologies. Here's a simple guide on how to use the calculator to its fullest potential and witness firsthand the impact it can have on your decision-making process.

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