Collecting most of their information from sensors, many agri-technology companies are harnessing the power of artificial intelligence to improve decision making.Is it helping production enhancement at low cost?Input requested.
If you own a smart Phone, then you are using artificial intelligence!
Artificial Intelligence (AI) has the potential to enhance and extend the capabilities of humans, and help businesses achieve more, faster and more efficiently.
Though by no means a new concept, several more recent developments have enabled AI to cross into the mainstream: namely, cloud computing, big data, and improved machine learning algorithms.
AI-driven analytics and real-time insights have already begun to help businesses grow their revenues and market shares faster than their peers in industries as diverse as healthcare, finance, utilities and e-commerce.
The Manufacturer’s Annual Manufacturing Report 2018 found that 92% of senior manufacturing executives believe that ‘Smart Factory’ digital technologies – including Artificial Intelligence – will enable them to increase their productivity levels and empower staff to work smarter.
A positive outlook for the future, perhaps, but uncertainty still exists. A recent survey by Boston Consulting Group found that a significant gap lies between an organisation’s ‘ambition and execution’, with only one in five companies incorporating AI into one or more of their processes.
Similarly, global research firm, Forrester says that 58% of business and technology professionals are researching AI systems, yet only 12% are actively using them.
So, to learn more about the opportunities Artificial Intelligence holds for manufacturing organisations, The Manufacturer spoke with Jamie Hall, senior solutions specialist for Microsoft.
How much and how fast will AI transform the manufacturing industry?
Manufacturers around the world are rapidly investing in the Internet of Things (IoT) to create new products and services, while driving down production costs over the longer term.
This transformation is changing the way companies think about how they engage their customers, empower their employees and optimise their operations.
However, delivering IoT is only part of the journey to achieving manufacturing excellence. For companies to realise the full potential of IoT, they need to combine the data collected from connected devices with rapidly advancing Artificial Intelligence to enable ‘smart machines’.
These will, in turn, simulate intelligent behaviour with little or no human intervention.
Predominantly, the AI in smart machines currently manages the more traditional repetitive tasks; however, this is advancing very quickly. The ability of AI to adapt to continuously changing tasks will move quickly into the mainstream, I expect.
This will be a paradigm shift from assisted intelligence swinging all the way across to full autonomous intelligence where machines are able to learn enough to make recommendations that humans can trust.
Besides smart machines on the shop floor, the use of AI and big data will be huge over the coming five years with dependable algorithms being used in all areas of an operation from weather prediction for the shipping of raw materials through to predictive maintenance of the resulting product.
AI techniques are actually replacing the costly machines, used for computations. Hence the low cost can be achieved.
At the same time,actual computation on the hardware is time consuming. Here, the AI reduces the required time drastically by replacing actual machines with the trained models based on AI techniques.
Artificial intelligence is already a reality in industrial applications. It helps make production more efficient and safer. Example is the identification of product failures from computational methods.
identification of product failures from computational methods is probably the most interesting and cost saving innovation. Many thanks dr Joao for input .
Yes, Artificial Intelligence has the potential to enhance production and it has the capabilities to achieve it more efficiently at low cost.
If you own a smart Phone, then you are using artificial intelligence!
thank u for recommendating my question.
- Mahesh Kumar
- Craig Refugio
- Han Ping Fung
- Beemnet Mengesha Kassahun
- Modestus Okwu
Artificial intelligence have a great important to increase production because it make easy the way of communication and exchange in the world
In my opinion, like playing chess, the more options you think (the source of data to choose from), the more likely it will be to get the BEST choise for the next step. That means it will provide a better "end result" (efficient production)
Here are topics from 135 articles with words " Artificial AND Intelligence AND (production* OR manufactur*) " in their titles. Each topic is represented by 20 words and 20 phrases through which it is discussed in these articles. In addition for each topic there are qotes from 2 documents in which it greatly represented.
We will be grateful for the feedback.
Hi Dr Silva
To add to your points Iike to point out that 'In the changing landscape of today’s global digital workspace, AI’s presence grows in almost every industry. Retail giants like Amazon and Alibaba are using algorithms written by machine learning software to add value to the customer experience. Machine learning is also prevalent in the new Service Robotics world as robots transition from blind, dumb and caged to mobile and perceptive'.thanks for your answer.
ajit
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Interesting input from Hon'ble RG members.Many thanks.
Finally,it may be said that although there have been many debates about replacing human intelligence with artificial intelligence, but, one cannot deny that the use of artificial intelligence increases productivity, especially in manufacturing.
ajit
Dear Ajit kumar Roy,
AI has the potential of enhancing production, it has practical and measurable value to any business whether in the area of e-commerce, manufacturing, retail, airport, media, healthcare or marketing and so on. It is capable of reducing cost while increasing productivity, profitability, efficiency and effectiveness at workplace.
Regards,
Modestus.
@Modestus-I agree with u that AI is capable of reducing cost while increasing productivity, profitability, efficiency and effectiveness at workplace. Really this is very good trend that means AI is going help sustainable production.
Absolutely, A.K. Roy. AI is very useful in sustainable production of manufacturing companies and service industries.
How Artificial intelligence improves production?
AI through its proposed decision / recommendation & control mechanism can improve / optimize production by improving the top lines e.g. product / service quality, speed go to market, market share, revenues gain etc., lower TCO & lower risk / meeting regulatory compliance etc.
Dear Dr. Ajit kumar Roy, it is an interesting question. One of the areas of AI contribution in production is in factories. Factories have changed considerably over the last century. One of the most significant changes to occur during this time has been the introduction of robots to the manufacturing process. AI can reverse the cycle of low profitability through intelligent automation and innovation diffusion.
AI helps discrete manufacturers unlock trapped value in their core businesses. Machine-based neural networks can understand a billion pieces of data in seconds, placing the perfect solution at a decision maker’s fingertips. Data is constantly being updated, which means implementing parties machine learning models will be updated, too. Companies will always have access to the latest information, including breaking insights, which can be applied to rapidly changing business environments.
https://www.themanufacturer.com/articles/power-artificial-intelligence-manufacturing/
https://www.mbtmag.com/article/2018/04/how-artificial-intelligence-redefining-manufacturing-industry
https://www.finextra.com/blogposting/15316/will-artificial-intelligence-modify-the-work-offices
https://www.devteam.space/blog/how-to-use-artificial-intelligence-to-improve-quality-control/
https://www.automationmag.com/technology/artificial-intelligence/7903-how-ai-and-machine-learning-are-reshaping-the-manufacturing-sector
https://schooledbyscience.com/artificial-intelligence-improving-mfg/
5 Ways Artificial Intelligence Is Improving Manufacturing
Source: https://schooledbyscience.com/artificial-intelligence-improving-mfg/
1. Artificial Intelligence Improves Product Management with Quality Objectives & Accurate Inventories.
Machine learning offers faster product management that is more accurate than employees. Its algorithms can analyze your goals for quality and then compare it to your production workflow and internal company processes.
Manufacturers often use artificial intelligence as a part of the Define, Measure, Analyze, Improve and Control (DMAIC) process because of its data-driven strategy to improve quality. The process also helps interpret and share the machine learning data with people unfamiliar with your production’s specific details.
Product mismanagement is common. Machine learning provides an effective solution to the frequent causes of mismanagement, such as human error, which can result in profit losses. Overstocked shelves lead to 3.2 percent lost income while out-of-stock inventory costs companies 4.1 percent.
2. Develop Preventative Maintenance with Integrated & Accurate Machine Learning
Maintenance is a part of manufacturing. Machine learning, however, offers a way to reduce the downtime of maintenance and repairs.
The technology, coupled with sensors, can monitor and predict when a machine will need maintenance and determine which component and parts will require it. Instead of your maintenance plan following a fixed schedule, it becomes adaptive to each machine’s needs. The data gathered is often incorporated into the Internet of Things (IoT) for users to access across platforms.
Machine learning improves maintenance and repair prediction substantially for some users. An automotive plant implemented machine learning to combat frequent machine failures. They’re now able to plan and predict a part failure within a 92 percent accuracy rate.
3. Upgrade OEE Management & Manufacturing efficiency with Condition Monitoring
Artificial intelligence enhances your Overall Equipment Effectiveness (OEE) management by monitoring equipment conditions across your entire plant.
Sensors and machine learning algorithms gather and analyze data to create a baseline for establishing failure probabilities, which they compare against your equipment’s ongoing, real-time operation. OEE and preventative maintenance are often interlinked improvements from machine learning.
The automotive plant mentioned above, for example, improved their predictive maintenance and boosted their OEE rate from the industry standard of 65 percent to a rate of 85 percent. Because of the increase, the plant improved their product quality and asset reliability.
4. Boost Yield Rates with Optimization & Predictive Data Analytics
Increased yield rates are an essential part of any business’s operation. Machine learning can assist in raising your yields in a few ways.
New manufacturing technology has given the industry smart systems. These systems are designed to coordinate and use machine learning to improve yield rates at local and global levels. The yields of your plants, production cells and equipment are all optimized using machine learning and predictive data.
Manufacturers producing customized and complex products also improve their yields via machine learning. The technology reviews and analyzes your needs to help you choose equipment and suppliers, as well as improve the function of those machines.
Companies, such as NVIDIA and FANUC, are developing artificial intelligence technology for the manufacturing industry. The two businesses are building industrial robots capable of teaching themselves how to improve their task completion times. The end goal is to streamline and improve production yields.
An eight-hour process for one robot, for example, would take a team of eight robots only an hour by working and learning together.
5. Enhance Supply Chains with Streamlined Production & Accurate Sale Forecasts
Manufacturing companies often won’t integrate their IT systems across plants, which can make sharing information across teams or company levels difficult. Machine learning streamlines the available data to provide accurate inventory information, delivery dates and sale forecasts.
Streamlined data also provides businesses with manufacturing information about their plants, inventories, Work In Process (WIP) and production lines. Because the data encompasses the entirety of the company, it offers insight into the overall status of the business and emphasizes possible improvements, future decisions or ability to meet sale forecasts.Sale forecasts predicted with machine learning have benefited several companies, such as Lennox International. Their initial forecast accuracy was around 55 percent before adopting machine learning. After implementation,
Sale forecasts predicted with machine learning have benefited several companies, such as Lennox International. Their initial forecast accuracy was around 55 percent before adopting machine learning. After implementation, their accuracy has reached 85 percent, and the technology has also found seasonal patterns and trends Lennox International was unaware of before.
Artificial intelligence is providing the manufacturing industry with new, helpful ways to adapt their production. Preventative maintenance, effective OEE management and increased yields all benefit a manufacturer directly, while streamlined supply chains and improved product management offer buyers or suppliers with enough products to meet predicted consumer demands.
Thank you A.K. Roy, please see the links below:
https://www.newgenapps.com/blog/ai-uses-applications-of-artificial-intelligence-ml-business
https://www.youtube.com/watch?v=va9IyKIETyY
https://www.forbes.com/sites/robertadams/2017/01/10/10-powerful-examples-of-artificial-intelligence-in-use-today/#31d85cde420d
Regards,
Modestus.
3 Ways Artificial Intelligence Can Improve Workplace Learning
My uncle once claimed he could magically tell you the day of the week if you gave him any calendar date (day, month and year). He said he could visually see the answer in his head and swore he didn’t have any quick calculation or trick. My father was skeptical. He bet my uncle $100 that he could develop an algorithm to do the same.
The next day, my father produced a page of calculations that, lo and behold, would produce the correct answer. I was in awe; my uncle was not as impressed. But, my dad still won the money.
What Is AI?
Algorithms have been around for thousands of years and are an essential and critical element behind artificial intelligence (AI). Algorithms are structured, step-by-step instructions, and computers are excellent in using algorithms at exceptional speeds. Scientists discovered that computers are not only fast with completing the calculations, but that they can also “learn” from them.
This is what’s called “machine learning,” which is a subset of AI. People give the system a goal and provide feedback along the way — an error for wrong behavior and a reward for favorable outcomes. Through these reinforcement signals, the system is able to “learn” an optimal approach to achieve the desired goal.
Because computers have the ability to scan vast amounts of data, process calculations and assess probabilities at lightning speeds, machine learning is quickly proving to be an incredible advancement that will tremendously impact our lives.
How Can AI Improve Workplace Learning?
Workplace learning — the ongoing leadership and skills development that takes place within a company—could stand to greatly benefit and improve with the right applications of AI. Here are a few three key ways I predict AI and machine learning will positively impact the experience of employees as learners:
1. Personalized and More Effective Learning Experiences
For many years now, the learning industry has touted the advantages of a more personalized learning experience. Now, with AI, this can be realized. Supported by back-end machine learning delivered through speech recognition and more intelligent user interfaces, the learner can experience more adaptation and tailoring to their specific needs and preferences.
Computers can do the behind-the-scenes data analysis and provide real-time feedback during a training experience, modifying a course path based on progress and response. Tests and quizzes can adapt to the learner’s inputs and intelligently recommend a tailored curriculum path. The learner gets a more efficient and personalized experience. Imagine: No more sitting in a five-day class if all the learner needs is just a portion of it.
2. Training Reinforcement
Surprisingly, we still don’t do a great job in training reinforcement. Yet, reinforcing the learning after a training event is critical to learning retention. (See my article on effortful recall for more details.) This is where machine learning and AI can make tremendous strides where humans have fallen short.
We don’t take time to reinforce learning — but computers can do it for us! Already, intelligent apps and systems are popping up in the marketplace that offer this. Like reminding us to take our vitamins, intelligent systems can engage us and help reinforce training, helping make the learning “stick” and increasing overall learning effectiveness as a result.
3. Measuring Effectiveness and ROI
Organizations have also failed in the area of measurement. With AI, we will have no excuse. Intelligent systems will be able to easily and quickly scan large quantities of data and pull from multiple sources, not just online assessments and course surveys. By correlating on-the-job activity in different existing systems with training programs, and even by matching employee profiles to create “buddy systems” and mentorships, AI will be able to help us modify training programs based on success and failure points. This will continuously improve the learning experience, so employees and trainers can focus on learning that actually produces results.
Make More Time for Meaningful Connection
All of these potential advancements will free up time for a company’s team that handles learning and development to focus on human interactions with employee-learners and think of new innovations and ideas in learning. The best strategy: Determine where computers and systems can automate the tedious tasks and analytics, so the team can provide more valuable human interactions with learners.
The potential is not far from reach: Different systems and authoring tools are already working to incorporate elements of machine learning. In addition, IBM Watson, Google Cloud Platform, AWS and others are providing developers with the ability to leverage these technologies to develop AI apps and engines that can feed into existing learning and development systems.
As David Clark, a senior research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory, says, “I like to consider [in using AI]…what problem needs a solution.” I believe making learning more personalized, reinforced and measured are three key “problems” or areas where machine learning, AI, and all the algorithms behind the two can make a huge impact in workplace learning. And, this would ultimately improve productivity and free up time and space for humans to focus on new ideas, innovations and each other.
My father would be proud of the advancements in AI and machine learning, and I know he would gladly hand over his algorithms to a computer. As a teacher himself, he’d say he preferred the human interactions over the time-consuming grading and tedious administrative tasks that kept him from focusing on new ideas and ways to inspire and teach.
I predict that AI won’t replace the teachers, but teachers who find ways to embrace AI will outlast, and be more effective and satisfied in their work, than those that don’t.
reference /https://bthechange.com/3-ways-artificial-intelligence-can-improve-workplace-learning-40b1185bc0d3
regards
Recommendation will strengthen me dear RG members.Many thanks.
@
- Mahesh Kumar
- Craig Refugio
- Han Ping Fung
- Beemnet Mengesha Kassahun
- Modestus Okwu
You are most welcome Ajit kumar Roy. Am glad to be part of this interesting discussion.
Regards,
Modestus.
Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving.
regards
Artificial Intelligence (AI) has the potential to enhance and extend the capabilities of humans, and help businesses grow faster and more efficiently. Just like the huge benefit experienced in manufacturing from Lean, automation and advanced IT, Artificial Intelligence will no doubt bring breakthrough in productivity improvement.
Regards,
Modestus.
Applying Artificial Intelligence in a typical manufacturing setting requires some key essential technologies. For instance, a well-designed factory will need to be networked, taking data from one system to another e.g from production lines, design room, fabrication unit and quality control unit to form an integrated, intelligent operation/process.
Hello,
Everything that surrounds us today – from our cars to our computers is the product of a mass production cycle on an assembly line. Over the last two decades, consumerism has not just exploded but reached unprecedented levels that have caught the biggest of manufacturers off guard. As the world enters a new era of consumer culture, organizations must be prepared to not just address growing consumer demands but also make sure that it is achieved in a cost-effective and profitable manner. But the big question is − how will global corporations strike the fine balance between production and quality control? How will they ensure that customer demands are met without compromising on the bottom line? The answer lies in Artificial Intelligence. Manufacturers around the world are rapidly investing in the Internet of Things (IoT) to create new products and services, while driving down production costs over the longer term. This transformation is changing the way companies think about how they engage their customers, empower their employees and optimise their operations. However, delivering IoT is only part of the journey to achieving manufacturing excellence. For companies to realise the full potential of IoT, they need to combine the data collected from connected devices with rapidly advancing Artificial Intelligence to enable ‘smart machines’. These will, in turn, simulate intelligent behaviour with little or no human intervention. Predominantly, the AI in smart machines currently manages the more traditional repetitive tasks; however, this is advancing very quickly. The ability of AI to adapt to continuously changing tasks will move quickly into the mainstream, we expect. This will be a paradigm shift from assisted intelligence swinging all the way across to full autonomous intelligence where machines are able to learn enough to make recommendations that humans can trust. Besides smart machines on the shop floor, the use of AI and big data will be huge over the coming five years with dependable algorithms being used in all areas of an operation from weather prediction for the shipping of raw materials through to predictive maintenance of the resulting product. With the right foundations in place manufacturers will see AI make many more informed decisions at each stage in the production process in real time. In the case of production, we will see sensors spotting defects on the production line. The data is then fed to the cloud to verify, which will immediately remove the defective part from the line and order a replacement all while calculating in real-time just-in-time schedules. With real-time problem-solving, manufacturers can potentially save millions of pounds in recalls, repairs and lost business. As use cases continue to evolve, AI will be pivotal in all areas of an organisation from fraud prevention to predictive ordering and opportunity assessment; all of which bring time, productivity and cost benefits which can be passed onto the customer. Each one of these intelligent insights will turn information into tangible outcomes. When combined with the Internet of Things, AI can also help proactively schedule appointments based on maintenance history. Manufacturing companies cannot afford to lose valuable time and productivity when there are unplanned equipment failures. Predictive intelligence provides an alert before machines break, enabling the company to preemptively schedule time to repair or replace a part without suffering any downtime, keeping the factory floor running on time and limiting disruptions.
Artificial intelligence is especially well suited for scheduling. The process of sending technicians to repair critical equipment is time consuming, tedious, and, if done using yesterday’s processes, an inefficient use of resources. That’s because a variety of factors affect the need to reschedule a service appointment, including inaccurate estimated travel time and work duration, incorrect or missing parts and even weather conditions. Schedule adjustments are typical, but for efficiency’s sake, they must be done quickly, and humans don’t always have the complete data to solve the problem expediently. Small issues turn into large logistical problems. Incorporating AI into your scheduling allows managers to estimate travel time and optimize the technician’s route, taking into account weather and traffic conditions. Based on history and task type, it can also flag customers that are a higher risk for cancellation and respond proactively and efficiently. This saves valuable time, not only for the technician, who can now attend to other work, but for customers too.
Reference
manufacturing.net, the manufacturer and techaspect.
An interesting issue. Currently, artificial intelligence is being developed in various service applications, in new online media, while in the sphere of production probably to a lesser extent. However, the possibilities of using artificial intelligence in production will gradually increase in the future. Similarly with other technologies of advanced information processing in the field of the current Industry 4.0 technological revolution, such as machine learning, Internet of Things, computerization of production logistics processes, application of Business Intelligence analytical platforms and Big Data database systems for the analysis of production processes in correlation with logistics deliveries and distribution logistics.
Best wishes
Artificial Intelligence improves production through operational efficiencies, reduced human errors reaching accuracy, attain cost saving by optimizing workforce and business process, Saves time and money by automating business processes and tasks, and quick decision making based on outputs and also create new business opportunities.
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