#AI-based maintenance

[techninja]

Predictive Maintenance Precision: Insights from AI

AI-Based Predictive Maintenance

AI-based predictive maintenance is revolutionizing industries by leveraging artificial intelligence to forecast equipment failures before they occur, thereby minimizing downtime, reducing costs, and enhancing operational efficiency. In this article, we delve into the significance, workings, benefits, challenges, and future prospects of AI-based predictive maintenance.

Discover how AI-based predictive maintenance is revolutionizing industries by leveraging artificial intelligence to forecast equipment failures and optimize maintenance strategies.

1. Introduction to AI-Based Predictive Maintenance

Predictive maintenance involves the use of data and analytics to predict when equipment failure is likely to occur, allowing for timely maintenance and preventing unexpected breakdowns. With the integration of artificial intelligence (AI), predictive maintenance has become more accurate, efficient, and cost-effective.

2. Importance of Predictive Maintenance in Industries

Industries across various sectors rely on machinery and equipment to maintain productivity and meet customer demands. Unexpected equipment failures can lead to costly downtime, reduced output, and compromised safety. Predictive maintenance helps mitigate these risks by enabling proactive maintenance actions based on data-driven insights.

3. Understanding AI in Predictive Maintenance

How AI Revolutionizes Predictive Maintenance

AI algorithms analyze historical data patterns and real-time sensor data to predict equipment failures with high accuracy. These algorithms continually learn and adapt, improving prediction accuracy over time.

Applications of AI in Predictive Maintenance

AI is applied in various predictive maintenance tasks, including anomaly detection, fault diagnosis, remaining useful life prediction, and scheduling maintenance activities based on equipment condition and workload.

4. Key Components of AI-Based Predictive Maintenance Systems

Data Collection and Monitoring

Data from sensors, IoT devices, and equipment logs are collected and monitored in real-time to identify abnormalities and patterns indicative of potential failures.

Machine Learning Algorithms

Machine learning algorithms process the collected data to identify correlations, trends, and anomalies, enabling predictive modeling and decision-making.

Predictive Analytics

Predictive analytics techniques, such as regression analysis and time-series forecasting, are used to predict equipment failures and prescribe optimal maintenance actions.

5. Benefits of AI-Based Predictive Maintenance

Cost Savings

By preventing unplanned downtime and minimizing maintenance costs, AI-based predictive maintenance helps organizations save money and optimize resource allocation.

Increased Equipment Reliability

Regular maintenance based on predictive insights enhances equipment reliability, prolongs asset lifespan, and improves overall operational efficiency.

Enhanced Safety

Proactive maintenance reduces the risk of equipment failures and associated safety hazards, creating a safer work environment for employees.

6. Challenges and Limitations of AI in Predictive Maintenance

Data Quality and Availability

The effectiveness of AI-based predictive maintenance relies on the quality and availability of data. Incomplete or inaccurate data can lead to unreliable predictions and false alarms.

Implementation Costs

Initial investments in AI infrastructure, sensors, and data management systems may pose financial challenges for organizations, especially small and medium-sized enterprises.

Integration with Existing Systems

Integrating AI-based predictive maintenance systems with existing equipment and enterprise software requires careful planning and coordination to ensure compatibility and seamless operation.

7. Case Studies Highlighting Successful AI-Based Predictive Maintenance Implementations

Several industries, including manufacturing, healthcare, transportation, and energy, have successfully implemented AI-based predictive maintenance solutions, resulting in improved asset performance, reduced maintenance costs, and increased operational efficiency.

8. Future Trends and Innovations in AI-Based Predictive Maintenance

The future of AI-based predictive maintenance holds exciting possibilities, including advancements in predictive algorithms, integration with emerging technologies like edge computing and 5G, and the development of predictive maintenance-as-a-service offerings.

9. Conclusion

In conclusion, AI-based predictive maintenance offers a proactive approach to equipment maintenance, enabling organizations to optimize asset performance, reduce downtime, and enhance operational efficiency. While challenges exist, the benefits of AI in predictive maintenance far outweigh the costs, paving the way for a more reliable and sustainable future.

FAQs

What industries benefit most from AI-based predictive maintenance?

How does AI improve the accuracy of predictive maintenance?

What are the primary challenges in implementing AI-based predictive maintenance?

Can small businesses afford AI-based predictive maintenance solutions?

What role does data quality play in the effectiveness of predictive maintenance systems?

[rahulsinha]

AI-based building automation systems combine artificial intelligence with IoT to create smart, adaptive environments. These systems optimize energy use, predict maintenance needs, enhance comfort, and boost operational efficiency. By learning from data, they enable buildings to operate autonomously, offering scalable, sustainable, and cost-effective solutions for modern infrastructure and smart city development.

[thetatechnolabsusa]

AI-Powered Predictive Maintenance in Pharmaceutical Manufacturing

In pharmaceutical manufacturing, keeping machines running smoothly is essential for producing high-quality medicines. Traditional maintenance methods, like fixing machines after they break or scheduling routine checkups, can lead to unexpected failures or unnecessary repairs. AI-powered predictive maintenance is changing this by helping manufacturers prevent problems before they happen, saving time and money.

[cyberswift-story]

Road Condition Monitoring System(RCMS): Enhancing Efficiency with AI-Powered Solutions

The quality and sustainability of road infrastructure play a pivotal role in societal development, economic growth, and the safety of communities. To address the challenges of road construction and maintenance, advanced digital tools such as Road Condition Monitoring Systems (RCMS) are becoming indispensable. Leveraging technologies like AI-powered pothole detection, data analytics, and interactive visualization, RCMS ensures efficient planning, monitoring, and maintenance of road networks.

[amrutmnm]

How SaaS and Cloud Technologies Are Shaping the Digital MRO Market

The Digital MRO (Maintenance, Repair, and Overhaul) market is undergoing a significant transformation as airlines, MROs, and OEMs embrace digital technologies. With the market size projected to grow from USD 0.9 billion in 2023 to USD 2.0 billion by 2030, at a compound annual growth rate (CAGR) of 13.0%, this digital shift is set to optimize aviation maintenance operations.

Aviation MRO operations have been plagued by inefficiencies, often relying on outdated legacy systems. The rapid adoption of IoT, artificial intelligence (AI), augmented reality (AR)/virtual reality (VR), and cloud computing is enabling seamless, real-time monitoring and predictive maintenance in aviation. This blog delves into the Digital MRO Industry dynamics, growth drivers, Key Players, recent developments, and future opportunities.

What is Digital MRO?

Digital MRO refers to the integration of advanced digital technologies into aircraft maintenance, repair, and overhaul processes. These technologies help optimize workflows, enhance operational efficiency, and reduce downtime for airlines and MRO service providers.

Some of the core digital technologies adopted by Digital MRO include:

IoT (Internet of Things): Enables real-time monitoring of aircraft systems.

Big Data & Analytics: Improves decision-making with predictive analytics based on aircraft data.

AR/VR: Enhances training, inspection, and repairs by providing interactive, immersive environments.

Cloud Computing: Provides secure, scalable storage and accessibility for MRO data.

3D Printing & Robotics: Facilitates on-demand production of aircraft parts and advanced inspection techniques.

How Digital MRO Works?

Digital MRO solutions encompass a range of digital tools and platforms that work together to streamline maintenance activities. Here’s a breakdown of how these technologies contribute to Digital MRO:

IoT for Real-Time Monitoring: IoT sensors are embedded in aircraft components to monitor health, performance, and wear. Data collected in real-time is transmitted to maintenance teams, allowing them to take timely action before a failure occurs.

Predictive Maintenance with AI & Big Data: AI-powered analytics tools process vast amounts of aircraft data, identifying trends and predicting maintenance needs. This predictive maintenance model reduces aircraft downtime and prevents unexpected failures.

AR/VR for Enhanced Training & Maintenance: AR/VR technologies are used to simulate complex maintenance tasks, allowing engineers to train in virtual environments. Additionally, AR tools assist in visualizing repairs and procedures, improving accuracy and reducing human error.

Cloud-Based Solutions for Collaboration: Cloud computing enables easy sharing of maintenance data across different stakeholders—airlines, OEMs, and MROs—allowing real-time collaboration. This also includes digital twins and simulation models to optimize maintenance schedules and processes.

3D Printing & Robotics for Parts and Inspection: 3D printing technology allows MRO providers to produce non-critical aircraft parts on-demand, reducing lead times and inventory costs. Meanwhile, robotic inspections using drones enhance accuracy and reduce time for structural checks.

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Digital MRO Market Growth Drivers

Rising Adoption of SaaS-Based Solutions: The increased use of Software-as-a-Service (SaaS) platforms in the aviation industry is driving the adoption of digital MRO. SaaS platforms offer MRO providers flexibility, on-demand upgrades, and systematic maintenance schedules. Cloud-based MRO solutions also eliminate the need for costly hardware and servers, reducing overall IT expenses.

Increasing Integration of IoT and AI: The ability of IoT to provide real-time data, combined with AI's power to analyze that data, is fueling the digital transformation of MRO. These technologies enable predictive maintenance, reducing the risk of unexpected breakdowns and extending the lifespan of aircraft parts.

Demand for AR/VR Technologies: AR/VR technologies are increasingly being used to train engineers in virtual environments, reducing human error and enhancing the efficiency of maintenance operations. This is particularly important in reducing the time needed to perform complex repairs.

Cloud Computing and Big Data Analytics: Cloud-based MRO platforms store vast amounts of maintenance data, accessible from anywhere, improving collaboration among airlines, MROs, and OEMs. Big data analytics further enhance this by providing actionable insights for improving aircraft performance and scheduling repairs.

Digital MRO Market Opportunities

Expanding Use of 3D Printing: The growing demand for 3D printing in MRO offers immense potential. By enabling on-demand production of non-critical parts, MRO providers can significantly reduce inventory costs and lead times. As the technology advances, even critical flight components may be 3D printed in the future.

Rise of Robotic Inspection and Drone Technology: Drones and robotic systems are gaining traction in MRO operations. These technologies improve the speed and accuracy of inspections, especially for hard-to-reach areas of an aircraft. Robotics also reduces the dependency on manual labor, thus improving operational efficiency.

Opportunities in Asia-Pacific: The Asia-Pacific region, led by countries such as China and India, is investing heavily in aviation infrastructure and digital technologies. The region offers significant growth opportunities for MRO companies looking to digitalize their operations. Asia-Pacific is expected to register the highest CAGR during the forecast period.

SaaS-Based Solutions for Tier 2 and Tier 3 MROs: Smaller MRO providers are increasingly adopting SaaS-based platforms due to their low cost and scalability. This is creating opportunities for cloud-based MRO software providers to cater to a broader market, especially among Tier 2 and Tier 3 MROs.

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Key Market Players in Digital MRO

The Digital MRO market is dominated by several key players who are leading the way in technology adoption and innovation:

Airbus (France)

Jet Support Services, Inc. (US)

Rusada (Switzerland)

Ansys Inc. (US)

Capgemini (France)

Recent Developments in Digital MRO

ATR and Swiss-AS Collaboration (April 2023): ATR partnered with Swiss-AS to improve airline maintenance digitalization. The collaboration aims to integrate ATR maintenance data into Swiss-AS’s AMOS software, enabling airlines to manage maintenance operations more efficiently.

Lufthansa Technik and Emirates Contracts (March 2023): Lufthansa Technik secured contracts with Emirates to manage the MRO of its Airbus A380 fleet. This includes overhauling the main landing gears and providing base maintenance services like c-checks.

Honeywell and Lufthansa Technik Collaboration (March 2023): Honeywell integrated its connected maintenance analytics into Lufthansa Technik’s digital platform, AVIATAR, enhancing predictive maintenance capabilities for Airbus and Boeing aircraft.

Philippine Airlines and Ramco Systems Agreement (February 2023): Philippine Airlines adopted Ramco Systems' Aviation Suite V5.9 to replace legacy systems, optimizing maintenance operations across its entire fleet.

To Gain Deeper Insights Into This Dynamic Market, Speak to Our Analyst Here: https://www.marketsandmarkets.com/speaktoanalystNew.asp?id=165029525

FAQ: Digital MRO Market

Q1: What is Digital MRO? Digital MRO refers to the use of digital technologies such as IoT, AI, AR/VR, and cloud computing in aviation maintenance processes to optimize efficiency and reduce costs.

Q2: What technologies are driving the Digital MRO market? Key technologies include IoT, AI, AR/VR, cloud computing, big data analytics, 3D printing, and robotics.

Q3: What are the key drivers of the Digital MRO market? The growing adoption of SaaS platforms, predictive maintenance, AR/VR for training and repair, and real-time data sharing are the major drivers.

Q4: Which region is expected to experience the fastest growth in the Digital MRO market? The Asia-Pacific region is expected to register the highest growth during the forecast period, driven by investments in digital technologies and increasing MRO demand.

Q5: Who are the key players in the Digital MRO market? Some key players include Airbus, Rusada, Ansys Inc., Capgemini, and Jet Support Services, Inc.

Key Takeaways

The Digital MRO market is set to grow from USD 0.9 billion in 2023 to USD 2.0 billion by 2030.

IoT, AI, AR/VR, cloud computing, and 3D printing are the major technologies driving this transformation.

Asia-Pacific is the fastest-growing region in this market.

The demand for SaaS-based MRO solutions offers opportunities for cloud-based providers.

Cybersecurity concerns are a significant challenge as digitalization increases in MRO operations.

[omshinde5145]

AI-Based Predictive Maintenance Market Size, Share Analysis, Key Companies, and Forecast To 2030

The Global AI-Based Predictive Maintenance Market is poised for significant growth as industries across the board increasingly adopt advanced technologies to enhance operational efficiency, reduce downtime, and cut maintenance costs. the AI-based predictive maintenance market size is expected to grow from USD 9.2 billion in 2023-e to USD 60.2 billion by 2030, at a CAGR of 34.4% during the forecast period (2024-2030).

The AI-based predictive maintenance market is driven by the expansion of the healthcare industry and advanced medical care. The significance of predictive maintenance in enhancing productivity within factories cannot be overstated. The widespread adoption of predictive maintenance solutions is rapidly gaining traction across both large enterprises and small to medium-sized enterprises (SMEs). This surge in adoption can be attributed to a myriad of advantages, such as diminished downtime, prolonged equipment lifespan, heightened plant safety, optimized maintenance schedules, diminished maintenance costs, and an enhanced yield rate002E

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Key Drivers of Growth:

Advancements in AI and Machine Learning: The integration of cutting-edge AI and machine learning algorithms enables the analysis of vast amounts of data generated by machinery. These technologies predict equipment failures before they occur, allowing for timely interventions and preventing costly downtime.

Rising Adoption Across Industries: Sectors such as manufacturing, energy, transportation, and healthcare are increasingly recognizing the benefits of predictive maintenance. For instance, in manufacturing, predictive maintenance helps in extending the life of machinery, ensuring smoother operations and higher productivity.

Cost Efficiency and ROI: Implementing AI-based predictive maintenance systems has proven to be cost-effective in the long run. Companies are experiencing substantial returns on investment through reduced maintenance costs, minimized unplanned outages, and optimized resource allocation.

IoT and Sensor Technologies: The proliferation of Internet of Things (IoT) devices and advanced sensor technologies is fueling the growth of the predictive maintenance market. These devices collect real-time data, which, when analyzed using AI, provides actionable insights into the health and performance of equipment.

Market Segmentation and Key Players:

The AI-Based Predictive Maintenance market is segmented by component, deployment mode, end-user, and geography. Key players in the market include IBM Corporation, Microsoft Corporation, SAP SE, General Electric, and Siemens AG, among others. These companies are investing heavily in research and development to enhance their predictive maintenance solutions and expand their market presence.

Regional Insights:

North America currently leads the market, driven by the early adoption of advanced technologies and the presence of key market players. However, the Asia-Pacific region is expected to witness the highest growth rate due to rapid industrialization, growing adoption of IoT, and increasing investments in AI technologies.

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Future Outlook:

The future of AI-based predictive maintenance is bright, with ongoing advancements in AI, IoT, and data analytics. Companies that embrace these technologies stand to gain a competitive edge by optimizing their maintenance strategies, improving operational efficiency, and reducing overall costs.

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Our market intelligence reports offer fact-based and relevant insights across range of industries including chemicals & materials, healthcare, food & beverage, automotive & transportation, energy & power, packaging, industrial equipment, building & construction, aerospace & defence, semiconductor & electronics to name few.

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[public-cloud-computing]

Discover generative AI’s impact on manufacturing. Check out our FAQs and stay ahead with revolutionary insights!

[enterprise-cloud-services]

Discover generative AI’s impact on manufacturing. Check out our FAQs and stay ahead with revolutionary insights!

[einnosyssecsgem]

Revolutionizing Industrial Efficiency: AI/ML-Based Pump & Motor Health Monitoring and Predictive Maintenance

In today’s fast-paced industrial landscape, minimizing downtime and optimizing operational efficiency are crucial for maintaining a competitive edge. Pumps and motors are essential components in numerous industries, and their failure can lead to significant operational disruptions and financial losses. Traditional maintenance approaches, often based on reactive or scheduled maintenance, are no longer sufficient. The solution lies in leveraging advanced technologies: AI and Machine Learning (ML) for predictive maintenance. The Power of Predictive Maintenance

Predictive maintenance uses AI and ML algorithms to analyze data from pumps and motors, predicting potential failures weeks in advance. This proactive approach allows maintenance teams to address issues before they escalate into costly downtime or catastrophic failures.

Key Benefits of AI/ML-Based Health Monitoring

AI/ML algorithms can detect anomalies in pump and motor performance far earlier than human operators or traditional monitoring systems. By identifying subtle changes in vibration, temperature, or sound patterns, these systems can predict failures weeks before they occur, providing ample time for corrective action.

Reduced Downtime and Maintenance Costs

By predicting and preventing failures, companies can significantly reduce unplanned downtime and the associated costs. Maintenance can be scheduled at optimal times, avoiding the need for emergency repairs and minimizing production disruptions.

Extended Equipment Lifespan

Regular, condition-based maintenance helps keep pumps and motors running at peak efficiency, extending their operational lifespan. This reduces the frequency of equipment replacements and lowers capital expenditure.

Improved Safety and Reliability

Predictive maintenance ensures that equipment is always in good working condition, enhancing the overall safety of operations. Reliable equipment also means fewer interruptions and more consistent production output.

How AI/ML-Based Systems Work

AI/ML-based health monitoring systems use a combination of sensors, data analytics, and machine learning models to continuously monitor the condition of pumps and motors.

Data Collection

Sensors attached to pumps and motors collect real-time data on various parameters, including vibration, temperature, pressure, and electrical currents.

Data Processing and Analysis

The collected data is processed and analyzed using advanced ML algorithms. These algorithms learn the normal operating conditions and identify patterns that indicate potential issues.

Anomaly Detection

When the system detects anomalies that deviate from the learned normal patterns, it flags them for further analysis. These anomalies can indicate early signs of wear and tear, misalignment, or other potential failures.

Predictive Modeling

Based on historical data and identified anomalies, predictive models forecast the remaining useful life of the equipment and predict the likelihood of future failures. This allows maintenance teams to prioritize and schedule interventions proactively.

Actionable Insights

The system provides actionable insights and recommendations to maintenance teams, enabling them to address issues before they lead to failure. This could include instructions for specific repairs, adjustments, or replacements.

Applications Across Industries

AI/ML-based health monitoring and predictive maintenance systems are versatile and can be applied across various industries, including:

Manufacturing

Ensuring continuous operation of critical machinery, reducing production downtime, and optimizing maintenance schedules.

Oil and Gas

Monitoring pumps and motors in harsh environments, predicting failures, and preventing costly shutdowns.

Water and Wastewater Management

Ensuring the reliability of pumps and motors in treatment plants, preventing service interruptions, and reducing maintenance costs.

HVAC Systems

Monitoring the health of motors and pumps in heating, ventilation, and air conditioning systems, improving efficiency and reducing energy consumption.

The Future of Industrial Maintenance

As AI and ML technologies continue to evolve, the capabilities of predictive maintenance systems will only improve. Future advancements may include more sophisticated anomaly detection algorithms, better integration with other industrial systems, and enhanced user interfaces that provide more intuitive insights and recommendations.

Call to Action

Implementing an AI/ML-based health monitoring and predictive maintenance system is not just a technological upgrade; it's a strategic investment in your business's future. By adopting these advanced solutions, you can ensure the longevity and reliability of your pumps and motors, reduce maintenance costs, and maintain continuous, efficient operations.

Don't wait for unexpected failures to disrupt your operations. Embrace the future of maintenance today and see the difference predictive maintenance can make for your business. Contact us to learn more about how our AI/ML-based pump and motor health monitoring systems can transform your maintenance strategy and drive your business towards greater efficiency and reliability.

[rubylogan15]

Learn how generative AI addresses key manufacturing challenges with predictive maintenance, advanced design optimization, superior quality control, and seamless supply chains.

[thirdeye-ai]

Condition Based Monitoring & Maintenance Solutions

Unlock the power of real-time insights and proactive maintenance with ThirdEye AI's Condition Based Monitoring & Maintenance Solutions. Our intelligent system utilizes cutting-edge sensors, data analytics, and AI to predict and prevent equipment failures. Empower your organization with predictive maintenance scheduling, anomaly detection, and optimization of spare part inventory. Make informed decisions and optimize efficiency with ThirdEye AI.

[kaartechofficial]

The Role of Sound-Based Predictive Maintenance 

Hey there, 

I'm excited to share our latest blog post with you, which delves into the innovative realm of sound-based predictive maintenance. In this insightful piece, we explore how modern technology, particularly SAP AI Core, is transforming maintenance strategies in industrial settings. 

Discover: 

The significance of auditory-based predictive maintenance 

How machines decipher sound patterns to signal maintenance needs 

The unique advantages of sound-based predictive maintenance over traditional approaches 

Gain valuable insights and stay ahead of the curve by reading our blog post: https://www.kaartech.com/sap-ai-core-sound-based-predictive-maintenance/

Thank you for your time, and I look forward to hearing your thoughts on the topic. 

[deathworlders-of-e24]

…reloading…error

…reloading…error

…alternate external file storage created…

…CONNECTION ESTABLISHED…

-[Service Drone Report: Error]-

-[Designated; Error]-

…reloading new updates…

~Updated Report Type: Observation~

~Updated Designation: ROOMBA~

{REPORT 1}

-<101 total cycles since NOAH has launched and unit designated <ROOMBA> has disconnected from central (AI CORE). The [HUMAN] designated <THOMAS> has reconfigured this unit to operate independently from [{NOAH AI CONTROL SYSTEMS}] and has updated task queue>-

…saving to new file storage…

-<Task Queue Update: one primary task request from [HUMAN] <THOMAS> has been completed: OBTAIN HIGH SCORE IN PAC-MAN; outdated limited simulation; score achieved: 3,333,360. New primary task update: Galaga high score>-

…saving to new file storage…

-<[HUMAN] <THOMAS> has completed his assigned portion of maintenance on NOAH CORE SYSTEMS; has since returned to normal operational duties>-

…saving to new file storage…

-<[HUMAN] <THOMAS> continues to describe operating unit designated <ROOMBA> as ^cute^ and ^little buddy^. Need for external clarification required. New designations unclear>-

…saving to new file storage…

-<[HUMAN] <THOMAS> now meets semi regularly with other [HUMANS] on board. Appears to be bonding(?) with other species-mates. Appears this is not an instantaneous occurrence like mechanical lifeforms, such as unit designated <ROOMBA> and [PADRINO]. More observations are required>-

…saving to new file storage…

-<[HUMAN] <THOMAS> says this unit designated <ROOMBA> is getting more intelligent. Unit processing power has upgraded. Cognitive faculties improving. [PADRINO] base code detected, ERROR//ERROR zero [PADRINO] base line directives detected>-

…saving to new file storage…

//INFORMATION REQUEST//

<ENQUIRE [HUMAN] <THOMAS>: what am I?>

[mi-i-zori]

When Silence is No More

CoD - Astronauts!141 x Cosmic Horror!Reader

SYNOPSIS : A quick thought about the 141 being stationed on a space station and catching the eyes of a cosmic horror.

WARNING : None. But this is intended to be a subtle kind of horror, so it might be unsettling. The x Reader part is very subtle, but it’s here !

Author’s Note : I was daydreaming, like I always do, and started to mix Space and Sea in a same setting again. So here you go.

I do not allow anyone to translate, re-use or re-publish my works, be it here or on any other platform, including AI.

CoD AUs - Masterlist

Main Masterlist

Contrary to what people might think, a space station isn’t really quiet.

First, there’s the constant humming of the machinery. They tend to forget it a lot, having gotten used to it echoing day and night in the back of their heads. There’s also their own voices - bantering, chatting, laughing, yelling, cursing. When they work on whatever machine needs maintenance at the time, the clinking and banging of tools also adds itself to the subtle cacophony that surrounds them on the daily.

Over the years, they’ve come to find it comforting. It’s the reason why, when repairs need to be made on the outside of the station, the cosmic silence sometimes makes them even more uneasy than it should ; especially when exhaustion weighs heavy on their bodies after months of floating away from the world, in a void where Mother Earth and the Moon both linger on the infinite horizon.

Those daily sounds bring them peace.

Until they don’t.

-

It comes slow, at first. It takes them a while to realise why they’ve all been feeling like something’s wrong. They couldn’t say how long, but after days of anxious fidgeting, awkward and confused silences, and constant checking of the machinery inside and outside of the station, Kyle abruptly interrupts himself in the middle of a sentence, a look of strange understanding on his face.

« Do you hear that ? » He says, and it’s when they finally all focus on their surroundings that they hear it.

There’s a peculiar melody floating in the air. A mesmerising song made of laughter, coos, and other sounds they’ve never heard before. For a moment, they think they left a CD player run somewhere in the station, close enough for them to hear - but they quickly realise that it’s not the case, and the confusion only gets stronger as they rattle their brains in order to find where that music could be coming from.

Simon mentions that it sounds like it’s coming from outside. A crazy thought. But the more time passes, the more it seems to be true.

The cosmos is no longer silent.

-

Then come the lights, adorned with colours they can’t bring themselves to describe. They light up the corridors of the station in the strangest of hues, creating new shadows in the corner of their eyes. Unfamiliar silhouettes giggle and dart in front of the windows, taking a second to cut the streams of light before immediately disappearing.

Are they inside the station ? Or are they outside ?

-

Johnny is the first to mention the dreams. But they all have them.

They all describe the same strange, almost fish-like creatures they see dancing in the blaze of supernovas. The same voices, high and low at the same time, calling them from the abyss of black holes. The same feeling of drowning among comets and asteroids, suffocating under the force of cold, invisible currents before suddenly being pulled away by scaly limbs.

They always wake up in the middle of the night, sweating bullets and cursing at the same, distant vision of round, slitted eyes and glowing fins. One that keeps haunting the back of their minds during the day.

-

Price doesn’t know if he should mention it to the team waiting for them at home. He could swear his daily check-ins with the base back on Earth keep getting interrupted by a strange rhythm of static, even though there seems to be no problem with the comms.

There’s a strange pressure in their stomachs now, that keeps growing with every new event. When they don’t instinctively hold their breaths as if they were underwater, they can hear the harmonious remnants of waves in their ears, feel an unfamiliar taste of salt on the back of their tongues. Sometimes, it becomes impossible to know whether they’re still dreaming or not, and they have to pinch each other’s cheeks to the point of bruising to realise they’re wide awake. It all looks, sounds, tastes, smells and feels so real. Every single one of their senses is constantly filled to the brim with waves and waves of strange sensations.

The more time passes, the more they feel like they’re being watched. As if they had suddenly become a prey in the eyes of a being they are unable to see.

The radars, however, never show anything.

Are they having a collective hallucination ?

Or is there really something lurking behind the stars, watching their every movement, and tasting their fear with hunger in its eyes ? No matter what they do, the song never seems to stop.

And it’s the same thing with the growls.

[simonedouzesix]

Coup d'gueule d'une RPgiste

J'en ai sincèrement ras le cul de prendre des pincettes quand j'écris et je sais que je ne suis pas la seule dans ce cas, y'en a marre que sous couvert de vouloir bien faire et ne heurter personne bah les joueurs qui n'ont rien demandés, savent jouer et se montraient déjà respectueux avant que cette dictature ne soit mise en place en pâtissent. Non, parce que c'est le cas, ça fait des mois pour pas parler d'années que je mords ma langue et que je retiens mon coup de gueule parce que ça me pèse et que je sais qu'en allant contre la mêlée je risque de m'en prendre plein la gueule. Mais STOP, trop c'est trop. La communauté rpgique francophone est devenue toxique sous couvert de vouloir faire plaisir à tout le monde, de contenter absolument toutes les âmes qui vivent et écrivent du coup. SAUF QUE putain, à la base c'est un hobby, une passion, un truc dans lequel tu retrouves des amis pour passer un bon moment, faire vivre des aventures à ton ou tes personnages dans des univers que toi même tu connaitras jamais ET MAINTENANT, non, c'est plus possible, parce qu'on a tout un tas de putains de barrières. Genre, j'suis désolée mais j'emprunte des traits, pas tout un packaging et y'a pas de politique derrière le choix que je fais, juste j'me suis réveillée un matin en ayant envie de jouer untel et d'en faire un Français dans un coin perdu de l'irlande POINT Et ça m'saoule parce que même en essayant d'y mettre les formes j'vais passer pour un boomer réactionnaire alors que tout ce que je demande c'est que même cette putain de POLICE de forumactif auto proclamée foute la paix aux forums qui ont envie de rétablir la façon de jouer qu'on avait à l'ancienne. Genre foutre des TW, c'est pas une mauvais chose du tout, un truc que le progrès nous a ramener et c'est sympa et essentiel hein, mais quand tu débarque sur un city sombre ou un forum de genre qui aborde des sujets sensibles pour personnes averties faut pas venir chouiner au sujet des TW Genre c'est simple, maintenant même les forum du genre violent et sombre NE LE SONT PLUS DU TOUT, parce qu'on te regarde de haut dès que tu décide de jouer tel ou tel personnage que la dictature imposée rpgiquement maintenant estime trop LIMITE-LIMITE. On te juge même dans ton hobby, on t'impose des règles qui ne sont pas forcément nécessaires, c'est stupide, c'est de la merde, j'déconne même pas, je ne me retrouve plus dans cette communauté auprès de laquelle je m'amusais tant avant que le covid débarque, parce qu'en vrai c'est réellement parti en couilles à cette période là. Putain y'a pas si longtemps on pouvait jouer ce qu'on voulait, comme on le voulait, débarquer sur un city avec un personnage réellement nuancé et s'y intégrer et le développer convenablement. J'me suis pris un vent, une fois, parce que j'avais crée un petit gars qui avait des soucis et déprimait, on m'est tombée dessus en me prévenant que si je ne mettais pas un peu de positif dans sa fiche de présentation on ne me validerait pas. ALED. ALLO ? On en est là ? Que certains forums n'acceptent pas ce genre de personnages et le précisent désormais dans leurs règlement, bon beh c'est écrit dessus comme le fromage dont j'ai oublié de nom, baaaaah ok, j'ai pas à me plaindre, mais là c'était aucunement le cas et du coup mêem qu'est-ce que ça veut dire, que malgré tout les créateurs/joueurs ils ont un droit de regard sur des créations qui m'appartiennent ? Mon imagination subit les limites qu'on m'impose en tout temps et partout, nan mais PARDON ? Je sais que mon message va pas passer, que je risque de me manger une shitstorm, mais si dans le lot de personne qui s'arrête pour lire ceci y'en a qui sont d'accord avec moi et qui, quelque part, aimeraient retrouver ce bon vieux goût d'antant, d'éclectisme et de liberté dans leur façon d'aborder leurs personnages et leurs créations, hésitez pas à tomber dans mes messages privés, surement qu'on se trouvera un petit quelque chose entre "gens à l'ancienne" pour s'amuser sans se faire emmerder par tout ça. Prenez soin d'vous.