Aerones is a Latvian robotics company focused on wind turbine inspection, maintenance, and repair. They use drones and crawler robots to check turbine blades inside and out. The systems handle lightning protection tests, drainage hole cleaning, visual inspections, and non-destructive testing. Aerones also provides robotic cleaning for blades and towers, removing dust, bugs, salt, algae, oil, and more. Robots can apply protective coatings, including ice-phobic and leading-edge coatings, directly on-site. A drone can scan a turbine in under 30 minutes with one button press. Data is uploaded to the cloud immediately and analyzed with AI to detect and classify issues. Compared to traditional methods, Aerones cuts downtime by 4–6 times and idle-stay periods by 5–10 times. Their technology is used worldwide by operators such as NextEra, GE, Vestas, Enel, and Siemens Gamesa, on both onshore and offshore turbines.
Medical device risk assessment isn’t just about what goes wrong but how it harms the patient/user ↴ Let's review some definitions: ✓ Harm = Injury or damage to the health of people, or damage to property or the environment. ✓ Hazard = Potential source of harm. ✓ Hazardous Situation = Circumstance in which people, property, or the environment is/are exposed to one or more hazards. ✓ Risk = Probability (P) of harm × Severity (S) of harm. Always remember: when answering ISO 14971, you're addressing this sequence: Hazard → Events → Hazardous Situation → Harm Note: One hazard can lead to multiple hazardous situations, which can lead to multiple harms. Don't forget that probability (P) can be split into: → P1 = Probability of a hazardous situation occurring. → P2 = Probability that situation causes harm. (This will be useful later.) Now, practical application: A device fails. A patient suffers. But was it direct harm… or indirect? That depends on your device.↴ Some devices fail, and the harm is immediate. Example: Hip prosthesis → A microcrack forms unnoticed. → The implant breaks inside the body. Direct Harm? ↳ Severe pain & immobility. ↳ Infection from broken implant fragments. Here's another example where the device isn’t the direct cause but still leads to harm. Example: Incorrect diagnostic output → A diagnostic device fails to detect a critical condition. → A clinician makes a wrong decision based on faulty data. → Outcome? Delayed/misguided treatment & more. To address indirect risks, I like to do this: → Assess risk across the entire system. → If multiple devices interact = System of Systems (SoS), analyze all interactions, sequence of events of your SoS (Device 1 ↔ Device 2 ↔ Patient) This is where splitting P1 & P2 can be a valuable strategy: → Helps understand event interactions. → Enables a combined risk approach for a comprehensive SoS risk assessment. I always ask myself this when evaluating an SoS: What is the probability of harm resulting from every hazardous situation? Need more for your medical device risk management ? Using our risk management template & methodology as a guide, you will be able to: → Use compliant process with ISO 14971 and MDR → Use a clear ISO 14971 methodology → Present your data clearly → Use tools proven in audits (our Hazard Traceability Matrix, RMP, and RMR). → Save time – no need to create templates from scratch. Our Risk Management bundle: https://lnkd.in/eTw2VVXp
Take control of medical device compliance | Templates & guides | Practical solutions for immediate implementation
Medical device risk assessment isn’t just about what goes wrong but how it harms the patient/user ↴ Let's review some definitions: ✓ Harm = Injury or damage to the health of people, or damage to property or the environment. ✓ Hazard = Potential source of harm. ✓ Hazardous Situation = Circumstance in which people, property, or the environment is/are exposed to one or more hazards. ✓ Risk = Probability (P) of harm × Severity (S) of harm. Always remember: when answering ISO 14971, you're addressing this sequence: Hazard → Events → Hazardous Situation → Harm Note: One hazard can lead to multiple hazardous situations, which can lead to multiple harms. Don't forget that probability (P) can be split into: → P1 = Probability of a hazardous situation occurring. → P2 = Probability that situation causes harm. (This will be useful later.) Now, practical application: A device fails. A patient suffers. But was it direct harm… or indirect? That depends on your device.↴ Some devices fail, and the harm is immediate. Example: Hip prosthesis → A microcrack forms unnoticed. → The implant breaks inside the body. Direct Harm? ↳ Severe pain & immobility. ↳ Infection from broken implant fragments. Here's another example where the device isn’t the direct cause but still leads to harm. Example: Incorrect diagnostic output → A diagnostic device fails to detect a critical condition. → A clinician makes a wrong decision based on faulty data. → Outcome? Delayed/misguided treatment & more. To address indirect risks, I like to do this: → Assess risk across the entire system. → If multiple devices interact = System of Systems (SoS), analyze all interactions, sequence of events of your SoS (Device 1 ↔ Device 2 ↔ Patient) This is where splitting P1 & P2 can be a valuable strategy: → Helps understand event interactions. → Enables a combined risk approach for a comprehensive SoS risk assessment. I always ask myself this when evaluating an SoS: What is the probability of harm resulting from every hazardous situation? Need more for your medical device risk management ? Using our risk management template & methodology as a guide, you will be able to: → Use compliant process with ISO 14971 and MDR → Use a clear ISO 14971 methodology → Present your data clearly → Use tools proven in audits (our Hazard Traceability Matrix, RMP, and RMR). → Save time – no need to create templates from scratch. Our Risk Management bundle: https://lnkd.in/eTw2VVXp
Risk Based Inspection in the age of Industry 4.0 Traditional Risk Based Inspection has served industry well, but the actual risk is not static. We assess risk at a point in time, then wait months or years before reassessing → hoping nothing significant changes in between. In the age of Industry 4.0 and Predictive Analytics, that approach is rapidly becoming obsolete. The evolution from traditional to monitoring-enhanced RBI represents more than just technological advancement → it's a fundamental shift in how we understand and manage asset integrity. Traditional RBI Foundations: Built on API 580 and 581 standards, traditional RBI provides structured frameworks for calculating Probability of Failure (PoF) and Consequence of Failure (CoF). These periodic, static assessments create inspection schedules based on risk rankings at specific moments in time. The monitoring enhanced Evolution: Modern RBI integrates real-time sensor data, predictive analytics, and machine learning to create dynamic risk profiles that evolve continuously. Instead of waiting for scheduled reassessments, risk calculations update automatically as conditions change. Here are the key technological enablers: → Smart sensors and IoT networks providing continuous condition monitoring → Data-driven FMEA models that identify failure patterns humans might miss → Predictive Analytics simulate degradation scenarios under various operating conditions → Risk visualization platforms that make complex data accessible to decision-makers API Standards Integration: This evolution aligns with existing API frameworks → 580/581 for quantitative risk modeling. The transformation delivers tangible benefits: earlier anomaly detection, optimized inspection planning, reduced costs, and enhanced regulatory compliance. Most importantly, it transforms risk management from a periodic exercise into a continuous capability. The technology exists today to make this transition. The question is not when but how fast the organizations will adopt this evolution or wait for others to prove its value. How is your facility preparing to integrate real-time data into your risk-based inspection strategy?
Risk Based Inspection in the age of Industry 4.0 Traditional Risk Based Inspection has served industry well, but the actual risk is not static. We assess risk at a point in time, then wait months or years before reassessing → hoping nothing significant changes in between. In the age of Industry 4.0 and Predictive Analytics, that approach is rapidly becoming obsolete. The evolution from traditional to monitoring-enhanced RBI represents more than just technological advancement → it's a fundamental shift in how we understand and manage asset integrity. Traditional RBI Foundations: Built on API 580 and 581 standards, traditional RBI provides structured frameworks for calculating Probability of Failure (PoF) and Consequence of Failure (CoF). These periodic, static assessments create inspection schedules based on risk rankings at specific moments in time. The monitoring enhanced Evolution: Modern RBI integrates real-time sensor data, predictive analytics, and machine learning to create dynamic risk profiles that evolve continuously. Instead of waiting for scheduled reassessments, risk calculations update automatically as conditions change. Here are the key technological enablers: → Smart sensors and IoT networks providing continuous condition monitoring → Data-driven FMEA models that identify failure patterns humans might miss → Predictive Analytics simulate degradation scenarios under various operating conditions → Risk visualization platforms that make complex data accessible to decision-makers API Standards Integration: This evolution aligns with existing API frameworks → 580/581 for quantitative risk modeling. The transformation delivers tangible benefits: earlier anomaly detection, optimized inspection planning, reduced costs, and enhanced regulatory compliance. Most importantly, it transforms risk management from a periodic exercise into a continuous capability. The technology exists today to make this transition. The question is not when but how fast the organizations will adopt this evolution or wait for others to prove its value. How is your facility preparing to integrate real-time data into your risk-based inspection strategy?
Many medical device development teams still rely on Design Failure Modes and Effects Analysis (DFMEA) as their primary risk assessment tool. Unfortunately, there are serious shortcomings to this method for medical device risk management: 🔹 Hazardous situations and harms can occur without any hardware or software failures (for example, due to use errors). Therefore, even a very detailed design FMEA is not comprehensive. 🔹 Typical DFMEA methods (per the IEC 60812 standard) focus on single point failures and do not capture sequences leading to harm. 🔹 DFMEA depends on details of hardware and software design that may not be available until later stages of development so there is a strong incentive to wait until later before beginning risk analysis. 🔹 DFMEA doesn’t align well with the requirements of the ISO 14971 risk management standard. DFMEA analyzes the reliability of a system, which may or may not cause Harm in a medical device. And RPN values used in a DFMEA can be misleading if they depend on detectability for reducing risk. 🔹 In a complex, software-intensive medical device there are many, many potential hardware/software failures but only a fraction of them may lead to serious Harm (it’s easy to lose focus in a large set of data). 🔹 DFMEA is an inefficient way to support complaint handling because users tend to complain about hazardous situations but not failures of hardware and software. I’m not saying there’s no role for DFMEA in medical device risk management, just that it shouldn’t be the primary method of risk assessment. Instead, I recommend starting early in product development with a top-down, high-level, comprehensive approach such as a System Hazard Analysis (sometimes called Preliminary Hazard Analysis) or Fault Tree Analysis (FTA) or similar method. This initial high-level analysis quickly produces a broad picture of the new product’s risk profile and can point to areas that deserve detailed bottom-up analysis with one or more focused DFMEAs. By starting early in development with a high-level risk analysis and following it with one or more DFMEAs, the product team makes the best use of complementary risk analysis tools. To better suit medical device safety risk management, it’s important to modify the standard DFMEA methodology and format. Columns for Hazardous Situation and Harm should be added to the FMEA table to align with the ISO 14971 risk model. And I recommend dropping RPN calculations altogether and just using a lookup table based on Severity and Probability of Harm to determine a Risk Level. What’s been your experience with DFMEA for medical devices? Any tips you would recommend to medical device teams? See comments for links to more detailed discussions of why DFMEA is often misused in medical device risk management.
Streamlined Compliance for Medical Device Development
Many medical device development teams still rely on Design Failure Modes and Effects Analysis (DFMEA) as their primary risk assessment tool. Unfortunately, there are serious shortcomings to this method for medical device risk management: 🔹 Hazardous situations and harms can occur without any hardware or software failures (for example, due to use errors). Therefore, even a very detailed design FMEA is not comprehensive. 🔹 Typical DFMEA methods (per the IEC 60812 standard) focus on single point failures and do not capture sequences leading to harm. 🔹 DFMEA depends on details of hardware and software design that may not be available until later stages of development so there is a strong incentive to wait until later before beginning risk analysis. 🔹 DFMEA doesn’t align well with the requirements of the ISO 14971 risk management standard. DFMEA analyzes the reliability of a system, which may or may not cause Harm in a medical device. And RPN values used in a DFMEA can be misleading if they depend on detectability for reducing risk. 🔹 In a complex, software-intensive medical device there are many, many potential hardware/software failures but only a fraction of them may lead to serious Harm (it’s easy to lose focus in a large set of data). 🔹 DFMEA is an inefficient way to support complaint handling because users tend to complain about hazardous situations but not failures of hardware and software. I’m not saying there’s no role for DFMEA in medical device risk management, just that it shouldn’t be the primary method of risk assessment. Instead, I recommend starting early in product development with a top-down, high-level, comprehensive approach such as a System Hazard Analysis (sometimes called Preliminary Hazard Analysis) or Fault Tree Analysis (FTA) or similar method. This initial high-level analysis quickly produces a broad picture of the new product’s risk profile and can point to areas that deserve detailed bottom-up analysis with one or more focused DFMEAs. By starting early in development with a high-level risk analysis and following it with one or more DFMEAs, the product team makes the best use of complementary risk analysis tools. To better suit medical device safety risk management, it’s important to modify the standard DFMEA methodology and format. Columns for Hazardous Situation and Harm should be added to the FMEA table to align with the ISO 14971 risk model. And I recommend dropping RPN calculations altogether and just using a lookup table based on Severity and Probability of Harm to determine a Risk Level. What’s been your experience with DFMEA for medical devices? Any tips you would recommend to medical device teams? See comments for links to more detailed discussions of why DFMEA is often misused in medical device risk management.
Hydrogen Production Plants Safety Studies: HAZID, HAZOP, QRA, LOPA, SIL and FEME 🟦 1) Green hydrogen production is set to increase rapidly, posing a significant challenge for the industry. Large-scale industrial water electrolysis plants use hydrogen and oxygen within the same equipment, separated by a membrane or diaphragm. Ensuring process safety is essential. In this post, I've summarized the safety study required for your green hydrogen project. 🟦 2) HAZID HAZID (Hazard Identification study) is a qualitative technique for identifying a process's main hazards. It involves using a block diagram or process flow diagram (PFD), which is used in the early stages of the design process. 🟦 3) HAZOP HAZOP (Hazard & Operability analysis) is a method to identify process hazards by analyzing deviations from normal conditions at the P&ID level. It focuses on equipment function loss and human error. Key elements of HAZOP sessions are: - Deviation - Cause of the deviation - Consequence of the deviation - Installed safeguards 🟦 4) Bow tie The bow tie method visually presents hazard scenarios, including the chain of events and barriers to prevent or mitigate scenarios. It is useful for internal and external communication of scenarios. 🟦 5) Risk matrix A risk matrix is used to assess the tolerability of a scenario based on the frequency and severity of undesired events. Likelihood is measured in frequencies per year, while consequences are defined by HSE impact and economic losses. The risk matrix determines the risk level. 🟦 6) Quantitative Risk Analysis (QRA) QRA is a method for calculating safety contours by considering the combination of fatalities and frequency. It involves determining the frequency of fatalities using tools like Fault Tree Analysis (FTA) and Event Tree Analysis (ETA). The consequence itself is determined using other tools, and all barriers that have an effect reduce the evaluated risk. 🟦 7) Level of Protection Analysis (LOPA) A small team further analyzes a subset of the most hazardous scenarios identified during a HAZOP, assessing the frequency and severity of the consequence. The basic principle of LOPA is that every safeguard may fail, so the consequence of the non-protected scenario cannot be eliminated. 🟦 8) Safety Integrity Level (SIL) SIL assessments are used to assign risk deduction factors to instrumental safeguards. The requirements for safety instrumented systems are given in IEC61508 and 61511. Four SIL levels are specified, with SIL 4 having a risk deduction factor of 10,000 to 100,000 and SIL 1 having a factor of 10 to 100. 🟦 9) Failure Mode and Effect Analysis (FMEA) FMEA focuses on equipment part failure and frequency to determine maintenance strategies. The accuracy of risk assessment depends on data quality. Source: See attached image. This post is based on my knowledge and is for educational purposes only. 👇 What other hydrogen safety study do you conduct? #hydrogen#Process#Safety
Hydrogen Production Plants Safety Studies: HAZID, HAZOP, QRA, LOPA, SIL and FEME 🟦 1) Green hydrogen production is set to increase rapidly, posing a significant challenge for the industry. Large-scale industrial water electrolysis plants use hydrogen and oxygen within the same equipment, separated by a membrane or diaphragm. Ensuring process safety is essential. In this post, I've summarized the safety study required for your green hydrogen project. 🟦 2) HAZID HAZID (Hazard Identification study) is a qualitative technique for identifying a process's main hazards. It involves using a block diagram or process flow diagram (PFD), which is used in the early stages of the design process. 🟦 3) HAZOP HAZOP (Hazard & Operability analysis) is a method to identify process hazards by analyzing deviations from normal conditions at the P&ID level. It focuses on equipment function loss and human error. Key elements of HAZOP sessions are: - Deviation - Cause of the deviation - Consequence of the deviation - Installed safeguards 🟦 4) Bow tie The bow tie method visually presents hazard scenarios, including the chain of events and barriers to prevent or mitigate scenarios. It is useful for internal and external communication of scenarios. 🟦 5) Risk matrix A risk matrix is used to assess the tolerability of a scenario based on the frequency and severity of undesired events. Likelihood is measured in frequencies per year, while consequences are defined by HSE impact and economic losses. The risk matrix determines the risk level. 🟦 6) Quantitative Risk Analysis (QRA) QRA is a method for calculating safety contours by considering the combination of fatalities and frequency. It involves determining the frequency of fatalities using tools like Fault Tree Analysis (FTA) and Event Tree Analysis (ETA). The consequence itself is determined using other tools, and all barriers that have an effect reduce the evaluated risk. 🟦 7) Level of Protection Analysis (LOPA) A small team further analyzes a subset of the most hazardous scenarios identified during a HAZOP, assessing the frequency and severity of the consequence. The basic principle of LOPA is that every safeguard may fail, so the consequence of the non-protected scenario cannot be eliminated. 🟦 8) Safety Integrity Level (SIL) SIL assessments are used to assign risk deduction factors to instrumental safeguards. The requirements for safety instrumented systems are given in IEC61508 and 61511. Four SIL levels are specified, with SIL 4 having a risk deduction factor of 10,000 to 100,000 and SIL 1 having a factor of 10 to 100. 🟦 9) Failure Mode and Effect Analysis (FMEA) FMEA focuses on equipment part failure and frequency to determine maintenance strategies. The accuracy of risk assessment depends on data quality. Source: See attached image. This post is based on my knowledge and is for educational purposes only. 👇 What other hydrogen safety study do you conduct? #hydrogen#Process#Safety
🙈 “Risks in the Shadow of Change“ 🙉 The basic goal of Management of Change (MOC) is to determine the risks brought by changes to be made in a hazardous process in advance, to eliminate or minimize these risks and to ensure that the change is implemented safely and sustainably. This approach is of vital importance, especially in technical areas. Because even a small change can have major consequences; it can cause rupture, leak, fire or even a major industrial accident. Unfortunately, many change approvers make decisions by evaluating this process only on paper. It is a common mistake to approve without seeing the reflection of the change in the field and without making the necessary analyses and observations. This can ironically turn change management into a process that creates risks rather than reducing risks. MOC is not only a procedural approval process, but also a critical discipline that requires technical expertise, field experience and a multi-faceted evaluation. Therefore, it is essential to adopt a multidisciplinary approach, especially in technical changes. Different areas of expertise such as mechanics, electricity, chemistry, operator, automation, occupational health and environment should come together to make an evaluation. Many industrial accidents in the past have resulted from the implementation of changes without sufficient analysis. For example, a small design change made in a pipeline may not be able to withstand the system pressure and may eventually cause explosions. Similarly, a small error made in software updates may hide alarms of processes that will create risks in PLC or DCS systems. In order to prevent such results, the MOC process must be supported by field observation, engineering calculations, and function tests. Although analyses on paper provide some basic insights, they cannot always reflect the complexity of real conditions. Therefore, conducting onsite inspections, interviewing employees, and observing the physical condition of equipment are critical steps. It should not be forgotten that change inherently involves uncertainty. This uncertainty can only be managed through a planned, systematic, and participatory MOC. It is necessary not only to analyze risks, but also to be prepared for these risks, to provide transparency in processes, and to create systems that can reverse change when necessary. Creating an effective MOC not only prevents accidents, but also paves the way for continuous improvement and innovation. Therefore, it is a critical requirement for change management practitioners to have field awareness as well as technical knowledge. #oil#gas#LPG#refinery#process#safety#learning#engineering#MOC#managementofchange#risks#riskassessment#terminal#safeoperation#safechange#LNG#oilandgas#evaluation.
+54K+ |Terminal Manager at Milangaz | Oil and Gas Industry Expert
🙈 “Risks in the Shadow of Change“ 🙉 The basic goal of Management of Change (MOC) is to determine the risks brought by changes to be made in a hazardous process in advance, to eliminate or minimize these risks and to ensure that the change is implemented safely and sustainably. This approach is of vital importance, especially in technical areas. Because even a small change can have major consequences; it can cause rupture, leak, fire or even a major industrial accident. Unfortunately, many change approvers make decisions by evaluating this process only on paper. It is a common mistake to approve without seeing the reflection of the change in the field and without making the necessary analyses and observations. This can ironically turn change management into a process that creates risks rather than reducing risks. MOC is not only a procedural approval process, but also a critical discipline that requires technical expertise, field experience and a multi-faceted evaluation. Therefore, it is essential to adopt a multidisciplinary approach, especially in technical changes. Different areas of expertise such as mechanics, electricity, chemistry, operator, automation, occupational health and environment should come together to make an evaluation. Many industrial accidents in the past have resulted from the implementation of changes without sufficient analysis. For example, a small design change made in a pipeline may not be able to withstand the system pressure and may eventually cause explosions. Similarly, a small error made in software updates may hide alarms of processes that will create risks in PLC or DCS systems. In order to prevent such results, the MOC process must be supported by field observation, engineering calculations, and function tests. Although analyses on paper provide some basic insights, they cannot always reflect the complexity of real conditions. Therefore, conducting onsite inspections, interviewing employees, and observing the physical condition of equipment are critical steps. It should not be forgotten that change inherently involves uncertainty. This uncertainty can only be managed through a planned, systematic, and participatory MOC. It is necessary not only to analyze risks, but also to be prepared for these risks, to provide transparency in processes, and to create systems that can reverse change when necessary. Creating an effective MOC not only prevents accidents, but also paves the way for continuous improvement and innovation. Therefore, it is a critical requirement for change management practitioners to have field awareness as well as technical knowledge. #oil#gas#LPG#refinery#process#safety#learning#engineering#MOC#managementofchange#risks#riskassessment#terminal#safeoperation#safechange#LNG#oilandgas#evaluation.
[ ⛳ Reverse Current & Over-voltage Protection ] 🤩 Learn How to Design a Reverse Current With Over-Voltage Protection Use a Comparator, a Zener diode, MOSFETs and few resistors ✨ 🤔 How does this circuit work? This circuit is based on a comparator and a P-Ch MOSFET. In order to turn "on" the P-Channel MOSFET, the gate must be brought "Low" below VBATT. To accomplish this, the comparator's Inverting input is tied to the battery side of the MOSFET to set the output low during forward current. R3 limits the gate current should there be any transients and should be a low value to allow the peak currents needed to drive the MOSFET gate capacitance. R2 provides the pull-down needed when the comparator output goes high-Z during power-off to ensure the gate is pulled to zero volts to turn off the MOSFET. The SHDN pin can be utilized to add Overvotlage Protection (OVP) by adding a second MOSFET, zener diode and resistor. When the SHDN pin is pulled 1.35 V above V-, the comparator is placed in shutdown. During shutdown, the comparator output goes Hi-Z and R2 pulls the gate and source together to turn off the MOSFET (VGS = 0 V). RPD pulls the SHDN pin low while the Zener diode is not conducting (< VZ). When ZD1 reaches its breakdown voltage and starts conducting, it will pull RPD up to a voltage calculated to place >1.35 V on the shutdown pin. 📌 Circuit Reference based on Texas Instruments p/n: TLV1805 comparator https://lnkd.in/eJwMK9Cj For this application, we need to choose a comparator with the following: ☑ with rail-to-rail input common mode range to enable high-side current sensing. ☑ with a push-pull output stage to efficiently drive the p-channel MOSFET. ☑ with low input offset voltage to optimize accuracy. 📌 Ideally, I'd consider using p/n: TPS25942A e-fuse by Texas Instrumentshttps://lnkd.in/eHeaycV7 which comes equipped with: ✅ Adjustable current limit ✅ Current monitoring ✅ Inrush current control ✅ Overvoltage protection ✅ Power good signal ✅ Reverse current blocking ✅ Short circuit protection ✅ Thermal shutdown. #circuitdesign#analogdesign#electronics#hardwaredesign#pcbdesign
Hardware | Systems Development in the Consumer Electronics | Industrial IoT
[ ⛳ Reverse Current & Over-voltage Protection ] 🤩 Learn How to Design a Reverse Current With Over-Voltage Protection Use a Comparator, a Zener diode, MOSFETs and few resistors ✨ 🤔 How does this circuit work? This circuit is based on a comparator and a P-Ch MOSFET. In order to turn "on" the P-Channel MOSFET, the gate must be brought "Low" below VBATT. To accomplish this, the comparator's Inverting input is tied to the battery side of the MOSFET to set the output low during forward current. R3 limits the gate current should there be any transients and should be a low value to allow the peak currents needed to drive the MOSFET gate capacitance. R2 provides the pull-down needed when the comparator output goes high-Z during power-off to ensure the gate is pulled to zero volts to turn off the MOSFET. The SHDN pin can be utilized to add Overvotlage Protection (OVP) by adding a second MOSFET, zener diode and resistor. When the SHDN pin is pulled 1.35 V above V-, the comparator is placed in shutdown. During shutdown, the comparator output goes Hi-Z and R2 pulls the gate and source together to turn off the MOSFET (VGS = 0 V). RPD pulls the SHDN pin low while the Zener diode is not conducting (< VZ). When ZD1 reaches its breakdown voltage and starts conducting, it will pull RPD up to a voltage calculated to place >1.35 V on the shutdown pin. 📌 Circuit Reference based on Texas Instruments p/n: TLV1805 comparator https://lnkd.in/eJwMK9Cj For this application, we need to choose a comparator with the following: ☑ with rail-to-rail input common mode range to enable high-side current sensing. ☑ with a push-pull output stage to efficiently drive the p-channel MOSFET. ☑ with low input offset voltage to optimize accuracy. 📌 Ideally, I'd consider using p/n: TPS25942A e-fuse by Texas Instrumentshttps://lnkd.in/eHeaycV7 which comes equipped with: ✅ Adjustable current limit ✅ Current monitoring ✅ Inrush current control ✅ Overvoltage protection ✅ Power good signal ✅ Reverse current blocking ✅ Short circuit protection ✅ Thermal shutdown. #circuitdesign#analogdesign#electronics#hardwaredesign#pcbdesign
Geotechnical Insights for Mining Projects Geotechnical studies are critical for open-pit and underground mining, addressing geological and engineering challenges throughout a mine's lifecycle. By analyzing the physical, structural, and hydrological properties of rocks and soils, these studies ensure operational efficiency, stability, and safety. 1. Importance of Geotechnical Studies Design Foundation: Provides data for designing stable slopes, safe excavation methods, and underground support systems Risk Mitigation: Identifies and mitigates hazards like slope failures, groundwater inflow, and stress-induced collapses Optimization: Aligns mine design with geological conditions to enhance efficiency and reduce costs Sustainability: Supports stable operations and safe closure, ensuring environmental sustainability 2. Key Geotechnical Parameters 2.1 Rock Mass Characterization RQD: Measures fracture intensity to assess the stability of tunnels, slopes, and excavations RMR: Evaluates rock mass quality, factoring UCS, joint conditions, groundwater, and orientation to guide slope and support design Q-System: Assesses underground stability, informing support and excavation decisions 2.2 Structural Geology Faults and Fractures: Critical for understanding stress redistribution and optimizing excavation Lithology and Alteration: Influences strength, permeability, and deformation, guiding design decisions Joint Orientation and Spacing: Controls block size, affecting slope and excavation stability 2.3 Hydrological Parameters Porosity: Indicates groundwater storage capacity and behavior Permeability: Essential for dewatering and managing groundwater risks Groundwater Inflow: Impacts operations, requiring drainage systems and grouting to manage risks 2.4 Rock Mechanics UCS: Measures rock strength under axial load, critical for excavation and support Shear Strength: Evaluates resistance to sliding, vital for slope and excavation stability Elastic Modulus: Defines rock deformation under stress, informing stability decisions Safety Factor: Balances forces to ensure stable, conservative designs 3. Applications Across Mining Phases Exploration: Geotechnical investigations guide rock property characterization and mine design Design: Data optimizes slope angles, excavation layouts, and underground openings Operation: Real-time monitoring ensures stability and timely adjustments Closure: Ensures long-term stability for reclamation and environmental safety 4. Risks and Mitigation Measures 4.1 Slope Failures Risks: Oversteepened slopes or poor conditions Mitigation: Bench designs, drainage, and monitoring 4.2 Groundwater Ingress Risks: Disrupts operations, increasing costs Mitigation: Dewatering, grouting, and predictive modeling 4.3 Stress-Induced Failures Risks: Roof collapses or pillar failures from stress Mitigation: Rock bolts, shotcrete, and stress modeling #MiningGeology#RockMechanics#SlopeStability#Hydrogeology
Exploration Geologist at International Resources Holding Company (IRH), Abu Dhabi, UAE.
Geotechnical Insights for Mining Projects Geotechnical studies are critical for open-pit and underground mining, addressing geological and engineering challenges throughout a mine's lifecycle. By analyzing the physical, structural, and hydrological properties of rocks and soils, these studies ensure operational efficiency, stability, and safety. 1. Importance of Geotechnical Studies Design Foundation: Provides data for designing stable slopes, safe excavation methods, and underground support systems Risk Mitigation: Identifies and mitigates hazards like slope failures, groundwater inflow, and stress-induced collapses Optimization: Aligns mine design with geological conditions to enhance efficiency and reduce costs Sustainability: Supports stable operations and safe closure, ensuring environmental sustainability 2. Key Geotechnical Parameters 2.1 Rock Mass Characterization RQD: Measures fracture intensity to assess the stability of tunnels, slopes, and excavations RMR: Evaluates rock mass quality, factoring UCS, joint conditions, groundwater, and orientation to guide slope and support design Q-System: Assesses underground stability, informing support and excavation decisions 2.2 Structural Geology Faults and Fractures: Critical for understanding stress redistribution and optimizing excavation Lithology and Alteration: Influences strength, permeability, and deformation, guiding design decisions Joint Orientation and Spacing: Controls block size, affecting slope and excavation stability 2.3 Hydrological Parameters Porosity: Indicates groundwater storage capacity and behavior Permeability: Essential for dewatering and managing groundwater risks Groundwater Inflow: Impacts operations, requiring drainage systems and grouting to manage risks 2.4 Rock Mechanics UCS: Measures rock strength under axial load, critical for excavation and support Shear Strength: Evaluates resistance to sliding, vital for slope and excavation stability Elastic Modulus: Defines rock deformation under stress, informing stability decisions Safety Factor: Balances forces to ensure stable, conservative designs 3. Applications Across Mining Phases Exploration: Geotechnical investigations guide rock property characterization and mine design Design: Data optimizes slope angles, excavation layouts, and underground openings Operation: Real-time monitoring ensures stability and timely adjustments Closure: Ensures long-term stability for reclamation and environmental safety 4. Risks and Mitigation Measures 4.1 Slope Failures Risks: Oversteepened slopes or poor conditions Mitigation: Bench designs, drainage, and monitoring 4.2 Groundwater Ingress Risks: Disrupts operations, increasing costs Mitigation: Dewatering, grouting, and predictive modeling 4.3 Stress-Induced Failures Risks: Roof collapses or pillar failures from stress Mitigation: Rock bolts, shotcrete, and stress modeling #MiningGeology#RockMechanics#SlopeStability#Hydrogeology
✅ Commissioning methodology refers to the systematic approach and procedures used to ensure that a system, facility, or equipment is installed, tested, and operated according to specified requirements before it is put into service. Commissioning is essential to verify that all components function correctly, meet performance criteria, and operate safely. Below is an outline of a typical commissioning methodology: ✅ Commissioning Methodology ✔️Planning Phase 🔹Scope Definition: Clearly define the scope of the commissioning process, including systems, components, and performance criteria. 🔹Commissioning Team Formation: Establish a multidisciplinary team with clear roles and responsibilities. 🔹Documentation Review: Review design documents, specifications, and requirements to ensure alignment. ✔️Pre-Commissioning Phase 🔹Inspection and Verification: Inspect equipment, components, and systems to ensure proper installation. 🔹Functional Testing: Conduct functional tests to verify equipment operation and interconnections. 🔹Calibration and Adjustment: Calibrate instruments and adjust settings as necessary. 🔹Safety Checks: Verify safety systems and emergency procedures. ✔️Commissioning Execution Phase 🔹System Testing: Perform integrated system tests to validate performance and functionality. 🔹Performance Testing: Conduct performance tests to ensure that equipment meets design specifications. 🔹Data Collection: Collect data on system performance for analysis and documentation. 🔹Training: Provide training to operators and maintenance personnel on equipment operation and maintenance. ✔️Documentation and Reporting 🔹Commissioning Reports: Prepare detailed reports documenting test results, issues identified, and resolutions. 🔹As-Built Documentation: Update record drawings, manuals, and other documentation to reflect actual installations. 🔹Punch List: Create a punch list of outstanding issues and track resolution progress. ✔️Acceptance and Handover 🔹Client Acceptance: Obtain client acceptance of commissioned systems based on predefined criteria. 🔹Handover to Operations: Transfer responsibility for the systems to the operations team. 🔹Post-Commissioning Support: Provide support to address any issues that arise during initial operation. ✔️Post-Commissioning Review 🔹Lessons Learned: Conduct a review to identify successes, challenges, and areas for improvement. 🔹Continuous Improvement: Implement feedback and lessons learned into future commissioning processes. 🔹Documentation: Update documentation with any changes or additions made during commissioning. ✅ A well-defined commissioning methodology is crucial for ensuring that systems and equipment are installed, tested, and operated efficiently and safely. By following a structured approach, potential issues can be identified and resolved early in the process, leading to smoother operations and reduced risks during the operational phase. Remaining text in Comment.............