How AI is changing the game of predictive maintenance

The amount of data that industrial companies have at their disposal today is more than ever before. When critical assets are in question, businesses should ideally be predicting and preventing issues before they happen by leveraging the data they possess.

The boom of the Internet of Things (IoT) and Artificial Intelligence (AI) has revolutionized businesses in all industries. Today, companies are making use of data to not only analyze the past but to make predictions about the future as well.

One area that leads to major cost savings and drives production value across industries is maintenance. Costs related to machine downtime is extremely high. The International Society of Automation estimated that $ 640 billion is lost worldwide every year due to machine downtime.

Maintenance processes have been revamped over the years with the aim of alleviating downtime and improving effectiveness. However, even today there is quite a bit of confusion as to what the best way is to use data with the aim of achieving optimum operational efficiency.  

Massive amounts of sensor data can be processed today much faster than before with the AI and machine learning solutions available today. This allows companies to improve their existing maintenance operations and innovate further and come up with something new – predictive maintenance.

One industry that will be affected massively by AI in terms of savings is manufacturing. Most manufacturers already have some form of preventive or predictive maintenance; however, AI can bring in a new age of productivity altogether.   

The next logical question you might have would be – how do ML, AI and data fit into your maintenance system in use at the moment? There are a few maintenance types and let’s have a look at the role that AI plays in each.

Total Productive Maintenance and AI

Total Productive Maintenance (TPM) – It is a complete system that includes maintenance and improvement of operational processes and critical assets which results in less downtime, lesser breakdowns, better safety and higher production.

This method has been used to complete the task of machine maintenance based on historical data and timetable data as to when repairs are required. Overall Equipment Effectiveness and plant productivity can be improved using total productive maintenance. When equipment maintenance is regular, breakdowns can be avoided, and asset uptime can be increased.  

Autonomous Maintenance – Adoption, Implementation and AI’s impact

Autonomous Maintenance is one of the major features of Total Productive Maintenance. Autonomous Maintenance ensures that everyone is responsible for performance of the machine and upkeep. Maintenance of the equipment is done by the operators of the machines themselves, instead of the maintenance technicians who were the only ones who used to take care of repairs.

This allows the maintenance technicians to focus on the bigger picture and increase the overall machine reliability. The challenging part of implementing AM is that it takes a lot of communication and training. The operators of the machines lack historical knowledge of the machines that the technicians have, and the technicians may not be too happy to give up certain tasks without seeing new job duties coming their way.

Today, businesses can leverage AI-driven software which allows for easier adoption of AM. The machine operators can now understand their machines better than before. With all the historical data available in one easy to access dashboard, everyone is on the same page and this allows for faster servicing of machines to be done. Artificial Intelligence ensures that every operator can get the job done with the right tools and the right knowledge at their disposal.

Preventive Maintenance vs. Predictive Maintenance

Maintenance which is influenced by events or time that necessitate repair is known as Planned Preventive Maintenance (PPM). Being a major component of TPM, in this system, maintenance is schedule during the runtime of equipment with the aim of reducing downtime and maximizing the productivity and lifespan of the equipment. This type of maintenance is not an exact science. There are certain drawbacks to it. The risk of over-maintaining and under-maintaining your assets is always there. This is because PPM does not take contextual information into account whereas it only relies on guidelines for routine check-ups.

Condition based indicators and alerts are used in predictive maintenance. These indicators and alerts throw up maintenance requirements only when the equipment is at risk of breaking down. This maximizes equipment availability and optimizes maintenance. Predictive Maintenance is usually performed when your equipment is still functioning but is at a high risk of failure.

Preventive and Predictive Maintenance with Data and AI

With data accessibility and connectivity becoming more widespread and cheaper across industries, companies are now turning to predictive maintenance powered by machine learning and advanced analytics solutions. As connectivity and data accessibility become cheaper and more widespread in industry, many companies are looking to predictive maintenance, or condition-based, maintenance, powered by machine learning and analytics.

Time based data is what predominantly drives PPM. Take the example of a car, maintenance schedules are determined based on the time that has passed or the kilometres driven. Data such as this allows you to compare how a specific asset is performing in comparison to similar assets. The data will only tell you what might happen. Many of the maintenance technologies in existence today only focus on transporting data and do aggregate it into real-time analytics. Sending of the data is only the initial step – what is done with this data is what really matters. AI and machine learning solutions can help aggregate and make use of your data much faster.

Data from various sources is used in predictive maintenance – sensor data from machines, historical maintenance records and weather data – to ascertain when a machine will need to be serviced. Operators can make informed decisions about when a machine will need repair by leveraging historical data as well as real-time asset data. Predictive maintenance amasses huge amounts of data and by making use of AI and predictive maintenance software’s, this data can be translated into useful data points and meaningful insights. This will help in avoiding data overload.  

The data that predictive maintenance amasses is messy – sensor data and machine-learning models make it possible to extract maximum value from this messy data extremely quickly. Sensor data and machine learning models are making it possible to quickly extract more value from large volumes of messy data.

Successful Implementation

The dark horse to implementing maintenance operations that are in sync with your business requirements is understanding the questions that you need answers to and figuring out how data can answer those questions. Questions may arise like – Do you just want to know what has occurred in order to plan the budget for the next year (or) How do you prevent unplanned downtime of equipment and lower costs?

Today, digitization is transforming businesses end-to-end. At the same time, you need to optimize your operations and make use of these tools apart from preventive maintenance, as making use of predictive maintenance tools have become imperative to survive. Technologies such as machine learning, artificial intelligence and predictive analytics are not just a luxury anymore – they are required to remain competitive, improve safety, reduce downtime and increase profits.

#machine-learning #deep-learning #artificial-intelligence

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Buddha Community

How Artificial intelligence is Transforming the Gaming Industry

First of all, the main question is: What is Artificial Intelligence in the gaming world? Artificial intelligence has been in the gaming industry since the beginning of video games. But the technology was so different now from then.

Artificial intelligence works with the NPC’s (non-playable characters), and is used to determine the behavior of the non-playable characters by generating the response or actions from the NPC’s. Artificial intelligence mainly works on interaction, so it does not include the firing, slashing, or killing an enemy.

What are NPC AIs?

A Non-Playable Character is like the protagonist’s friend or family member, or it can be anybody in the game. In most games today, the NPC AIs don’t really use machine learning technology, because they don’t have to. If there are 4 dialogue options to choose from and 1 NPC response to each option, this can be achieved with traditional computer programming. There is no need for machine learning here.

In terms of traditional NPCs, we use the term AI because these characters are supposed to be made in a way that they appear real and alive.

The main work of an NPC is to help the player to advance in the storyline or to say something about the tasks of the game or different places the player has to go or how to defeat a certain enemy. They are controlled by artificial intelligence, as with the help of artificial intelligence an NPC adapts the behavior of the player and generates human-like responses which help in the progression of the mission or storyline.

For example, RDR2 (Red Dead Redemption 2) is one of the great games which has shown us the true power of artificial intelligence. The whole storyline has beautifully shown us the importance of NPCs in a game and how they adapt from the player’s different decisions and the storyline changes from those decisions. In short words, artificial intelligence determines the player’s behaviors and emulates the behavior of the NPC’s to make the storyline meaningful.

Now on to the main question.

#gaming #gaming-industry #ai #transform #ai-in-gaming #ai

Lakshya Pareek

Lakshya Pareek


How to Create a Successful Gaming App?

How to create a game app is a comprehensive guide, explaining the entire process of creating and publishing games for iOS and Android. Covering all the essential information a budding game developer needs to know.


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#game-engine  #game-development  #game  #games  #gaming 

Juned Ghanchi


AI in Game Development - ITChronicles

For some years, artificial intelligence (AI) has been penetrating almost all digital spaces. After playing an instrumental role in digital communication and real-time problem-solving in many industries, AI in game development is expanding too. The significant impact of AI has played an instrumental role in the mobile and console game industry’s success.

AI has taken game development to new heights. AI helps to ensure greater satisfaction for gamers by addressing their objectives and concerns. AI also helps game developers come with higher-value additions and revisions based on data-driven insights,

AI is now showcasing many unprecedented opportunities in the gaming industry besides fulfilling its primary promise of delivering a great gaming experience. Here are some of the key ways AI is affecting the development of modern games.

**AI-Based Player Profiling **

Game developers now include AI-based player profiling within the game frameworks. This offers a game-playing experience that suits the target player profiles’ characteristic elements. You can hire game developers in India who are experts in creating AI-based player profiles equipped and thoroughly trained with game playing styles and different in-game player behaviors. These talented game developers can deliver a highly real-life environment within the game thanks to precise player profiling based on AI technology.

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#game development #game programming #game algorithms #game character design

Lakshya Pareek

Lakshya Pareek


How Much Does AI Game Development Cost?

The gaming industry is one of the fastest-growing industries in the world that has been leveraging the power of emerging technologies and facilitating constant innovations. The advent of advanced technologies like AI and ML has revolutionized the industry. Nowadays, these technologies are prevalent in online games and help enhance the overall experience of the game. Artificial Intelligence in games provides plenty of benefits for businesses as well as users. This lucrative technology is responsible for creating highly responsive games in which game characters evolve with the storyline. Moreover, these games also don’t burn a hole in your wallet as they don’t hike up the ludo game app development cost

Artificial Intelligence makes the game more responsive and interactive. Adding features like self-learning NPCs, increasing the game complexity, AI chatbots and more, Artificial Intelligence is a widely used technology in the gaming industry. 

Now that we’ve established that AI is a beneficial technology, you must be wondering about the AI Game Development Cost. Fret not, this article will highlight the factors that affect the cost of developing an AI game and the cost of developing an AI game. 

How is AI utilized in Gaming?

Artificial Intelligence has plenty of benefits in gaming. The technology is responsible for making responsive and competitive games that offer an overall immersive gaming experience to users. Moreover, it is necessary for integrating NPCs with learning capabilities. Let’s take a look at the various applications of AI in gaming. 

  • Integrating NPCs with learning capabilities
  • Decision-based storylines
  • Pathfinding feature
  • Data Mining
  • Content Generation
  • Player Experience Modelling
  • Cheating and Increasing Difficulty

Now that you have learned about the various applications of AI in gaming. Let’s take a look at the various factors that affect the game app development cost. 

Factors Affecting AI Game Development Cost

There are many factors that come into play when estimating the AI game development cost. Many factors must be taken into account to determine the exact development cost of an AI game. Let’s take a look at the factors. 

Location of the Developers

The location of the developers plays an important role and majorly influences the overall game development cost. Different regions of the world have different costs for developers. India-based Developers are significantly cheaper than USA-based Developers. 

  • India-based Developers: $30-$50 per hour
  • UK-based Developers: $100-$150 per hour
  • Australia-based Developers: $70-$120 per hour
  • USA-based Developers: $150-$250 per hour

Features of the Game

The features of the game also play an important role in determining the AI development cost. It goes without saying that the more features you include, the higher the game development cost will be. However, features are an important factor that enhances the interactivity of the game and are integral in attracting gamers. That is why it is recommended to only include features that are absolutely necessary and not to over-clutter the AI game with unnecessary features that don’t fit in. 

The complexity of the Game

This is probably the most important factor as the complexity of the game will majorly influence the game app development cost. If you are building a hypercasual game, you can complete the development process for a few thousand dollars. However, if you are planning to make an AAA game, you will have to invest millions of dollars. So, choose wisely and decide beforehand what type of game you want to create. 

Cross-platform Compatibility

If you are developing a game app that is supported by multiple platforms, it will significantly hike up the development cost. Single-platform games are fairly cheaper to develop when compared to multi-platform games. Different platforms require different developers, technologies, and tools. This is why cross-platform support hikes up the game development cost considerably. If you want to develop a cross-platform game, your best bet is to find a game development company that offers affordable cross-platform game development. 

Graphics and Visuals

It is important to pay special attention to graphics if you want to curb the cost of game development. Heavy and intensive graphics will definitely hike up the cost of development. Meanwhile, if you are developing a simple hypercasual game, graphics don’t really matter as long as the gameplay and storyline are engaging. However, if you want to develop a complex game title with sophisticated features and functionalities, your game must also include impeccable graphics. 

Technology Stack

The technology stack of the game also majorly impacts the game development cost. As mentioned earlier, different platforms require different technologies and require different developers. As a game operator, you will have to buy different technologies depending on your platform and developer’s expertise and that will directly factor in the game development cost. So choose the platform and tech stack beforehand to complete the process within an estimated budget. 

Artificial Intelligence Game Development Cost

As stated above, there are various factors that must be taken into account to determine the overall AI game development cost. Even after factoring in all the factors, it is difficult to provide an exact estimate without factoring in the client’s requirements. If you are looking for an exact cost quotation you will have to contact an AI game development company

On average, the AI game development cost ranges from $40,000 to $50,000 for a single-platform game with basic features. However, if you want to develop a cross-platform game with sophisticated features, you will have to invest close to $100,000 to $150,000 depending on the type of game you want to develop. 

Final Words

Game development is an expensive and time-taking process. Developing an AI game requires the collective efforts of the development team and includes a variety of resources. If you want to develop a game integrated with Artificial Intelligence and are still not afraid of the game app development cost, you should contact an AI game development company.

#artificial-intelligence #ai #game-development #games #game app development 

Otho  Hagenes

Otho Hagenes


Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution