What do you do if artificial intelligence is revolutionizing the manufacturing industry?

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Artificial intelligence (AI) is transforming the manufacturing industry in many ways, from automating tasks and optimizing processes to enhancing quality and innovation. But how can you adapt to this new reality and leverage the benefits of AI for your business? Here are some tips to help you navigate the AI revolution in manufacturing.

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Conduct a SWOT analysis:

Understanding your business's strengths, weaknesses, opportunities, and threats is key to leveraging AI. This strategic planning can guide where and how to implement AI effectively in manufacturing.
Demystify AI vs. robotics:

Clarify the distinction between AI and robotics to optimize their use. Recognizing that not all automated processes require AI helps focus on areas where true AI, like data analysis, can make a significant impact.

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1 Understand AI

AI is not a single technology, but a broad term that covers various applications of machine learning, computer vision, natural language processing, and other methods that enable machines to perform tasks that normally require human intelligence. AI can help you improve your productivity, efficiency, accuracy, safety, and customer satisfaction by automating repetitive, complex, or hazardous tasks, analyzing data and patterns, detecting defects and anomalies, generating insights and recommendations, and creating new products and services.

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PHIL FRIEDMAN?

Social Media Marketer - Marine Industry Consultant - Writer/Editor - YachtbuildAdvisor.com - 88K+ total SM subscribers and followers - 1,600+ Published Articles
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One of the first things to understand is that Artificial Intelligence (Ai) is not the same as robotics. There are may processes in manufacturing that have been, or in the near future will be robotized (automated). It is a mistake, however, to lump them in with far fewer aspects of manufacturing that are susceptible to being taken over by Ai. It is also important to demand strict proof of concept when it comes to Ai in manufacturing processes, because not even a highly successful CRM system, powered by Ai, can be used as a model for self-learning manufacturing. The bottom line is understand precisely what Ai is and what it isn't.

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Nicola La Motta

Director Water Platform Innovation
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AI capability is an enchantment and extension of our domain knowledge . However do not forget that without good data it is completely useless. So first get structured data and then think about AI to get get valuable insights

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2 Assess your needs

Before you invest in AI solutions, you need to identify your business goals, challenges, and opportunities. What are the pain points and gaps in your current operations? What are the areas where you can improve your performance and competitiveness? What are the customer expectations and market trends that you need to meet or anticipate? You can start by conducting a SWOT analysis (strengths, weaknesses, opportunities, threats) and a gap analysis (current state vs desired state) to evaluate your situation and define your priorities.

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3 Choose your solutions

Once you have a clear vision of your needs and objectives, you can explore the different AI solutions that are available and suitable for your industry and domain. You can either develop your own AI systems, using tools and platforms such as TensorFlow, PyTorch, or Azure AI, or take advantage of ready-made AI solutions from vendors and providers. For example, predictive maintenance leverages sensors, data, and algorithms to monitor equipment condition, predict failures, and schedule maintenance. Quality control uses cameras, image recognition, and deep learning to inspect products, identify defects, and ensure quality standards. Demand forecasting employs historical data, market analysis, and machine learning to predict customer demand, optimize inventory, and plan production. Smart design combines generative design, simulation, and optimization to create new products and prototypes that meet specific criteria and constraints.

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4 Implement and integrate

Once you've chosen your AI solutions, you must implement and integrate them with your current systems and processes. This may necessitate technical, operational, and organizational changes, such as upgrading infrastructure and equipment to support AI capabilities and connectivity, training personnel to use and maintain the AI systems and tools, adjusting workflows and policies to the new AI processes and outputs, establishing clear roles for human-machine collaboration, and monitoring the performance and impact of the AI solutions.

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Kandhasaami Nallayan

CEO at Bharathi lifestyles (Sustainable Innovation for Textiles) Founder of SATISFACT Revolutionizing AI tool for Textile Manufacturers and Exporters Founder of CAN I HELP YOU Create Leaders for the Business World
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Please don’t try to overhaul your entire operation at once. Begin by implementing AI in a specific area where it can have a significant impact. This allows you to gain experience and assess the benefits before scaling up. A variety of AI solutions are available, from cloud-based platforms to on-premise software. Carefully evaluate your needs and resources when selecting the most suitable tools for your manufacturing operation.

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5 Learn and improve

AI is not a one-time project, but a continuous journey of learning and improvement. You need to keep up with the latest developments and trends in AI technology and applications, and constantly test, measure, and refine your AI solutions to ensure they meet your changing needs and goals. You also need to collect feedback and data from your customers, employees, and partners to understand how they perceive and benefit from the AI solutions, and how you can enhance their experience and satisfaction. By doing so, you can leverage the full potential of AI for your manufacturing business.

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Kandhasaami Nallayan

CEO at Bharathi lifestyles (Sustainable Innovation for Textiles) Founder of SATISFACT Revolutionizing AI tool for Textile Manufacturers and Exporters Founder of CAN I HELP YOU Create Leaders for the Business World
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Keep ourselves updated on the latest advancements in AI for manufacturing. Attend industry events, conferences, or webinars to learn from experts and stay ahead of the curve. Consider collaborating with AI startups or established technology companies to explore and implement cutting-edge AI solutions for your specific needs.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Nicola La Motta

Director Water Platform Innovation
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Think about AI as a member of your team. You need to get to learn him/her first and then start collaborating to solve businesses problems

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PHIL FRIEDMAN?

Social Media Marketer - Marine Industry Consultant - Writer/Editor - YachtbuildAdvisor.com - 88K+ total SM subscribers and followers - 1,600+ Published Articles
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Always strive to keep Ai in perspective, notwithstanding the marketing hype that attends it. Be careful of turning control over to any given instantiation of Ai, until the system has been parallel tested with your standard operating procedures and well proven. And keep in mind that with computer software implementations, he who pays completely before the implementation is full, complete, and thoroughly tested (way past the Beta stage), inevitably ends up paying again and again to complete a system that was not ready when it was delivered. Always have a payment hold-back in the contract pending final proof of a complete and successful implementation.

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What do you do if artificial intelligence is revolutionizing the manufacturing industry?

1

2

3

4

5

6

1 Understand AI

2 Assess your needs

3 Choose your solutions

4 Implement and integrate

5 Learn and improve

6 Here’s what else to consider

Manufacturing

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What do you do if artificial intelligence is revolutionizing the manufacturing industry?

1

2

3

4

5

6

1 Understand AI

2 Assess your needs

3 Choose your solutions

4 Implement and integrate

5 Learn and improve

6 Here’s what else to consider

Manufacturing

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