These metrics help in mitigating risks associated with robotic operations, protecting workers, and optimizing robot performance. KPIs support the safe and effective integration of robotic technology into various industries. They are key for organizations to harness the benefits of robotics while ensuring the safety and well-being of their workforce.
KPI |
Definition
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Business Insights [?]
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Measurement Approach
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Standard Formula
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Automated Emergency Shutdown Reliability More Details |
The reliability of automated emergency shutdown systems in robotic systems, crucial for safety as stated in ISO 10218.
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Provides insight into the reliability of the emergency shutdown systems integrated into robotic equipment.
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Measures the percentage of successful automated shutdowns in emergency situations.
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(Number of Successful Automated Emergency Shutdowns / Total Number of Emergency Shutdowns) * 100
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- An increasing failure rate of automated emergency shutdown systems may indicate potential safety hazards and the need for system maintenance or upgrades.
- A decreasing failure rate could signal improved system reliability and safety measures being effectively implemented.
- Are there specific components or areas within the automated emergency shutdown system that are more prone to failure?
- How does the failure rate of our automated emergency shutdown system compare with industry standards or best practices?
- Regularly conduct maintenance and testing of the automated emergency shutdown system to identify and address potential issues before they escalate.
- Invest in advanced technologies or upgrades to enhance the reliability and responsiveness of the automated emergency shutdown system.
- Provide comprehensive training for personnel responsible for monitoring and managing the automated emergency shutdown system to ensure proper utilization and timely response in emergency situations.
Visualization Suggestions [?]
- Line charts showing the trend of failure rates over time.
- Pareto charts to identify the most common causes of failures within the automated emergency shutdown system.
- High failure rates in the automated emergency shutdown system pose significant safety risks to personnel and equipment.
- Repeated failures may lead to regulatory non-compliance and potential legal consequences.
- Condition monitoring systems to track the performance and health of critical components within the automated emergency shutdown system.
- Failure mode and effects analysis (FMEA) software to systematically identify and mitigate potential failure modes in the system.
- Integrate failure rate data with maintenance management systems to schedule proactive maintenance and minimize downtime.
- Link failure rate analysis with risk management processes to prioritize and address high-risk failure modes within the automated emergency shutdown system.
- Improving the reliability of the automated emergency shutdown system can enhance overall safety performance and reduce the likelihood of accidents or incidents.
- However, investing in system upgrades or maintenance may incur additional costs and resource allocation.
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Automated Material Handling Efficiency More Details |
The efficiency of material handling processes that are automated by robots, assessed by throughput and error rates.
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Sheds light on the effectiveness of automation in optimizing material flow and reducing manual intervention.
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Measures the throughput rate and accuracy of automated systems in material handling processes.
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(Units Handled Correctly by Automated System / Total Units Handled) * 100
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- An increasing throughput with stable error rates may indicate improved efficiency in the automated material handling processes.
- A decreasing throughput coupled with rising error rates could signal operational issues or technical malfunctions in the automated material handling systems.
- Are there specific areas in the material handling process where errors tend to occur more frequently?
- How does the throughput and error rates compare during peak production periods versus off-peak periods?
- Regularly maintain and calibrate the robotic systems to ensure optimal performance and minimize errors.
- Implement continuous monitoring and analysis of the material handling processes to identify and address any bottlenecks or inefficiencies.
- Invest in training programs for employees to effectively operate and oversee the automated material handling systems.
Visualization Suggestions [?]
- Line charts showing the trend of throughput and error rates over time to identify any correlations or patterns.
- Pareto charts to prioritize and address the most common sources of errors in the material handling processes.
- High error rates can lead to damaged products, production delays, and potential safety hazards.
- Consistently low throughput may result in backlogs, increased lead times, and customer dissatisfaction.
- Robot performance monitoring software to track and analyze the efficiency and error rates of the automated material handling systems.
- Quality control and inspection technologies to identify and address any defects or issues in the handled materials.
- Integrate the automated material handling efficiency data with production scheduling systems to optimize the workflow and minimize downtime.
- Link the error rates with maintenance management systems to schedule timely repairs and prevent potential breakdowns.
- Improving automated material handling efficiency can lead to cost savings, increased productivity, and enhanced overall operational performance.
- However, changes in the KPI may require adjustments in staffing, training, and maintenance budgets to sustain the improvements.
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Automated Safety Monitoring Adoption Rate More Details |
The rate of implementation of automated safety monitoring systems in robotic applications, aligning with ISO 10218's emphasis on continuous safety.
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Reveals the degree of modern safety technology integration and potential areas for increased adoption of automated monitoring.
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Tracks the percentage of automated safety monitoring systems implemented in the organization's robotic operations.
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(Number of Automated Safety Monitoring Systems Implemented / Total Number of Safety Monitoring Systems Possible) * 100
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- Increasing adoption of automated safety monitoring systems may indicate a growing awareness of safety standards and regulations within the industry.
- A decreasing adoption rate could signal a lack of prioritization for safety measures or challenges in implementing the required technology.
- Are there specific areas or processes where automated safety monitoring systems are not being utilized effectively?
- How does the adoption rate align with the overall safety performance and incident reports within the organization?
- Invest in training and education to ensure proper understanding and utilization of automated safety monitoring systems.
- Regularly review and update safety protocols to integrate new technologies and best practices.
- Consider incentives or rewards for departments or teams that demonstrate exceptional adherence to safety standards through automated monitoring systems.
Visualization Suggestions [?]
- Line charts showing the trend of adoption rates over time.
- Comparison bar charts displaying adoption rates across different departments or locations.
- Low adoption rates may lead to increased safety incidents and potential regulatory non-compliance.
- Over-reliance on manual safety monitoring in lieu of automated systems can pose risks to employee well-being and operational continuity.
- Robot safety monitoring software such as RoboGuard or SafetyEye for real-time monitoring and analysis.
- Integration with existing robotic control systems to streamline safety monitoring and response processes.
- Linking safety monitoring data with incident reporting and corrective action systems for comprehensive risk management.
- Integrating safety monitoring with production scheduling to ensure minimal disruption while maintaining safety standards.
- Improving the adoption rate of automated safety monitoring systems can lead to a safer work environment and reduced risk of accidents, positively impacting employee morale and productivity.
- However, increased adoption may also require initial investment in technology and training, impacting short-term financial performance.
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CORE BENEFITS
- 132 KPIs under ISO 10218
- 15,468 total KPIs (and growing)
- 328 total KPI groups
- 75 industry-specific KPI groups
- 12 attributes per KPI
- Full access (no viewing limits or restrictions)
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Automation Scalability Index More Details |
A measure of how easily the existing robotic systems can be scaled up or down in response to production demands.
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Highlights the flexibility of the manufacturing setup to meet changing demands and the potential for expansion.
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Considers the ease and cost-effectiveness with which the current automation system can be scaled up or down.
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(Total Cost of Additional Automation / Increase in Production Capacity) * 100
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- An increasing automation scalability index may indicate a need for greater production capacity or a shift towards more automated processes.
- A decreasing index could signal challenges in integrating new robotic systems or a reduction in production demand.
- What are the specific factors that limit the scalability of our current robotic systems?
- How does the automation scalability index align with our overall production planning and capacity utilization?
- Regularly assess the performance and capacity of existing robotic systems to identify potential scalability issues.
- Invest in flexible and modular robotic solutions that can easily be expanded or reconfigured to meet changing production demands.
- Implement predictive maintenance practices to ensure that robotic systems are consistently operating at their optimal capacity.
Visualization Suggestions [?]
- Line charts showing the trend of the automation scalability index over time.
- Stacked bar charts comparing the scalability index across different production lines or facilities.
- Low automation scalability can lead to production bottlenecks and inefficiencies during periods of increased demand.
- Overestimating scalability without proper planning can result in underutilized robotic systems and wasted resources.
- Simulation software to model the impact of scaling up or down robotic systems on production processes.
- Data analytics tools to monitor and analyze the performance of robotic systems and identify scalability opportunities.
- Integrate the automation scalability index with production scheduling systems to ensure that robotic systems can adapt to changing production plans.
- Link the index with maintenance management systems to proactively address scalability issues and prevent downtime.
- Improving automation scalability can lead to increased production efficiency and lower unit costs, but may require initial investment in new robotic technologies.
- Conversely, a low scalability index can limit the ability to respond to market demands and may result in missed production opportunities.
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Autonomous Decisions by Robots More Details |
The number of decisions made autonomously by robots without human intervention, which can be a measure of advanced AI implementation in robotics.
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Reflects the level of intelligence and autonomy integrated into robotic systems, which can indicate potential for reduced human oversight.
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Tracks the number of decisions made by robots without human intervention.
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Total Number of Autonomous Decisions Made by Robots / Total Number of Decisions Required
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- An increasing number of autonomous decisions by robots may indicate advancements in AI capabilities and greater trust in robotic autonomy.
- A decreasing trend could signal issues with AI implementation, lack of confidence in robotic decision-making, or a shift towards more human intervention.
- What types of decisions are being made autonomously by robots, and are they aligned with organizational goals and safety standards?
- How do the autonomous decisions by robots compare to those made by humans in terms of accuracy, efficiency, and adaptability?
- Regularly assess and update the AI algorithms and training data to ensure accurate and reliable autonomous decision-making.
- Implement fail-safe mechanisms and human oversight for critical or high-risk decisions to prevent potential errors or safety hazards.
Visualization Suggestions [?]
- Line charts showing the trend of autonomous decisions over time to identify patterns and anomalies.
- Comparative bar graphs displaying the distribution of autonomous decisions across different categories or functions.
- Highly autonomous decision-making without proper safeguards can lead to errors, accidents, or unintended consequences.
- Over-reliance on robotic autonomy may result in reduced human oversight and accountability, posing ethical and legal risks.
- AI and machine learning platforms for continuous learning and improvement of robotic decision-making capabilities.
- Simulation and testing software to validate and optimize autonomous decision algorithms in controlled environments.
- Integrate autonomous decision data with quality control systems to ensure that robotic decisions align with product and process standards.
- Link robotic decision-making with predictive maintenance systems to anticipate and address potential issues before they impact operations.
- Improving the accuracy and efficiency of autonomous decisions can enhance overall operational productivity and reduce human error.
- However, over-reliance on robotic autonomy may lead to reduced human skill development and job displacement, impacting workforce dynamics.
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Autonomous Mobile Robots (AMRs) Penetration Rate More Details |
The percentage of material handling and movement tasks performed by AMRs, reflecting the level of warehouse automation.
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Indicates the degree of modernization and efficiency in material handling and intra-logistics.
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Measures the proportion of AMRs in use compared to the total number of mobile robots.
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(Number of AMRs in Operation / Total Number of Mobile Robots) * 100
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- Increasing penetration rate may indicate a shift towards more automated warehouse operations and improved efficiency.
- Decreasing rate could signal challenges in implementing AMRs or a lack of scalability in the current automation strategy.
- What are the specific material handling tasks that are being successfully performed by AMRs?
- How does the AMR penetration rate align with the overall warehouse automation strategy and goals?
- Invest in training and education for employees to effectively integrate AMRs into daily operations.
- Regularly assess and update the AMR technology to ensure it meets the evolving needs of the warehouse.
Visualization Suggestions [?]
- Line charts showing the AMR penetration rate over time to identify trends and patterns.
- Comparison charts to visualize the distribution of material handling tasks between AMRs and traditional methods.
- Low AMR penetration rates may indicate underutilization of automation potential and inefficiencies in material handling.
- High penetration rates without proper maintenance and oversight can lead to increased downtime and operational disruptions.
- Warehouse management systems with AMR integration capabilities for real-time tracking and performance analysis.
- Data analytics tools to monitor AMR utilization and identify areas for improvement.
- Integrate AMR performance data with inventory management systems to optimize stock movement and storage.
- Link AMR utilization with workforce management systems to ensure efficient task allocation and resource utilization.
- Increasing AMR penetration can lead to reduced labor costs and improved operational efficiency.
- However, over-reliance on AMRs may impact the flexibility and adaptability of the warehouse workforce.
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In selecting the most appropriate ISO 10218 KPIs from our KPI Library for your organizational situation, keep in mind the following guiding principles:
It is also important to remember that the only constant is change—strategies evolve, markets experience disruptions, and organizational environments also change over time. Thus, in an ever-evolving business landscape, what was relevant yesterday may not be today, and this principle applies directly to KPIs. We should follow these guiding principles to ensure our KPIs are maintained properly:
By systematically reviewing and adjusting our ISO 10218 KPIs, we can ensure that your organization's decision-making is always supported by the most relevant and actionable data, keeping the organization agile and aligned with its evolving strategic objectives.