Halo’s Post

The world of color is evolving 🎨. As Strategic General Manager in a Chemical Manufacturing firm, I've seen firsthand how high-quality pigment paste and powder are revolutionizing industries from paints, coatings, automotive to fashion. The key trends driving innovation include: - Sustainability ♻️: Developing products that are Eco-friendly and safe. - Customization 🔧: Creating tailored solutions for unique customer needs. - Technology Integration 💡: Leveraging AI and machine learning for color matching and formulation. How do you see these trends impacting your industry? #ChemicalManufacturing #Innovation #PigmentTechnology #IndustryInsightTuesday#TintingSystemCompany#TSC

#AI, Fictiv introduces and demonstrates new AI capabilities & mold flow library at NPE2024 Fictiv, a global manufacturing company with manufacturing centers in Mexico, India, China, and the USA, will debut innovations for its Injection Molding offerings at this year's NPE2024 show in Orlando. The show is hosted by the Plastics Industry Association, and Fictiv will be in Booth S26140.   As artificial intelligence continues to transform nearly every industry, Fictiv is introducing Materials.AI for Injection Molding, revolutionizing material selection for production parts. The new OpenAI-powered tool is freely accessible on the Fictiv platform to assist users with optimal material selection based on mechanical properties, desired tool life, or end-use application of customer parts. Materials.AI for Injection Molding further delivers on Fictiv's promise to simplify sourcing for custom manufacturing, accelerate new product introduction, and ensure manufacturing quality.   Fictiv is also launching the first-of-its-kind Mold Library, which helps engineers and supply chain teams digitally track their tool inventory, quickly re-order parts, and look up the remaining tool life based on historical part production, and enabling companies to manage/depreciate tools as they do for other assets in their business. #RB,#AI

Embrace the power of machine learning to revolutionize your paper manufacturing processes and stay ahead in a competitive landscape! #kemira #machinelearning #predictiveanalytics

📢📌 Webinar on CFD simulations and AI for extrusion process 🚀💻 Would you like to optimise your know-how in the development, design and maintenance of dies for polymer extrusion process? Join our upcoming webinar in October to find out about the #digitaltwin solutions from our partner IANUS Simulation GmbH. 📆 When? 2 dates, on Thursday 12th of October or on Thursday 26th of October at 11 am CEST (same content on both dates) ⏳ How long? 1 hour 📍 Where? Online with Gotowebinar (registration link in the comments ⤵ ) We will cover specific examples and discuss how simulation combined with artificial intelligence algorithms will help industries reduce their carbon footprint by using less virgin plastic and more recycled plastic. Not only in extrusion but in all types of transformation processes. We hope to see you online at this webinar! 🚀💻 #webinar #ai #simulation #manufacturing #recycledplastic

Those looking at the plastics industry from the outside may think it's an old enough field that we have it all figured out - not true! Check out this work co-authored by some of SABIC's superstars (Vaidya Ramakrishnan, Ph.D. (He/Him/His) and Andre Van Zyl) to read more about the complexity of materials, and how machine learning is playing a critical part in innovation.

🔧 𝐂𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐢𝐧𝐠 𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡𝐞𝐬 𝐟𝐨𝐫 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐒𝐞𝐦𝐢𝐜𝐨𝐧𝐝𝐮𝐜𝐭𝐨𝐫 𝐄𝐪𝐮𝐢𝐩𝐦𝐞𝐧𝐭 🌟 . . . In the semiconductor industry, a one-size-fits-all approach to component lifecycle management is like trying to use a cricket bat in a football match—ineffective! ⚽🏏 Each type of equipment—from etchers and deposition tools to lithography systems—has unique requirements that demand tailored lifecycle strategies. 🎯 💡 𝐖𝐡𝐲 𝐂𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐌𝐚𝐭𝐭𝐞𝐫𝐬: ✳ 𝐄𝐭𝐜𝐡𝐞𝐫𝐬: 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: High susceptibility to wear due to chemical processes. ⚗️ 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Frequent monitoring and predictive maintenance to address component degradation, ensuring precision and minimizing downtime. ⏱️ ✳ 𝐃𝐞𝐩𝐨𝐬𝐢𝐭𝐢𝐨𝐧 𝐓𝐨𝐨𝐥𝐬: 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: Delicate balance of deposition rates and uniformity. ⚖️ 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Advanced analytics to track usage patterns and component health, ensuring timely replacements and maintaining performance standards. 📊 ✳ 𝐋𝐢𝐭𝐡𝐨𝐠𝐫𝐚𝐩𝐡𝐲 𝐒𝐲𝐬𝐭𝐞𝐦𝐬: 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: Extreme precision required for patterning. 🎯 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Real-time monitoring of critical components and leveraging AI for predictive insights to extend the lifecycle of key parts, maintaining accuracy and efficiency. 🤖 📈 𝐓𝐡𝐞 𝐑𝐞𝐬𝐮𝐥𝐭: 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐚𝐧𝐝 𝐑𝐞𝐝𝐮𝐜𝐞𝐝 𝐃𝐨𝐰𝐧𝐭𝐢𝐦𝐞 By customizing lifecycle management approaches, semiconductor manufacturers can achieve 𝐠𝐫𝐞𝐚𝐭𝐞𝐫 𝐞𝐪𝐮𝐢𝐩𝐦𝐞𝐧𝐭 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲, 𝐫𝐞𝐝𝐮𝐜𝐞𝐝 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐜𝐨𝐬𝐭𝐬, 𝐚𝐧𝐝 𝐩𝐫𝐨𝐥𝐨𝐧𝐠𝐞𝐝 𝐮𝐩𝐭𝐢𝐦𝐞, leading to more efficient and cost-effective operations. 🏭💡 If you’re curious about how to optimize lifecycle management for your specific tools, I’d love to connect and chat! 🤝 #Semiconductors #SemiconductorProductManagement #BrightBytesWithRitam 𝐏𝐢𝐜𝐭𝐮𝐫𝐞 𝐬𝐨𝐮𝐫𝐜𝐞: Wired

Automated materials testing helps improve productivity and exponentially increases the number of tests that can be performed over a short period of time. Automation is efficient and enables a company to use valuable personnel resources far more effectively, part of which is establishing the proper framework to apply to your own manufacturing process #testing #automation #TiniusOlsen #Manufacturing #automationsolution #automationtesting #automationsystems #roboticarm #innovation #tech #AI #industrialautomation #automationengineering #automationcontrol #robotarm #automationequipment #efficiency #industrial #MaterialScience #Engineering #MaterialsEngineering #technology #automationsolution #MechanicalEngineering #laboratory https://lnkd.in/eKa6wh9X

UNCOUNTABLE NOUN Know-how is knowledge of the methods or techniques of doing something, especially something technical or practical. Synonyms: expertise, experience, ability, skill      It is the most valuable intellectual property a company possesses, and the most difficult to pass on to the next generation, because it is based on knowing how to do things practically before theoretically.   Taking risks and learning from one's mistakes, rinse and repeat as BDL has been doing for nearly 50 years of working in the plastics injection molding industry, whether it is mold making or molding.   The new investments that we have been carrying on since last three years are all about latest technologies for AI based CNC and press machines as it should be if we want to keep pace with current challenges, but for not loosing our step we need to transfer our know-how into the AI system.   That’s going to be an interesting acronym AIKH or KHAI to be pronounced as ouch   Here at BDL we wonder if its acronym (AIKH or KHAI) should really be read as OUCH   #bdlmouldmaker #bdlinjectionmolder #medicalmolds #pharmaceuticalmolds #packagingmolds #aisolutions #moldsknowhow

🚀 Understanding Bias, Noise, Errors, Variance, and the Bias-Variance Tradeoff in Industrial Processes 🚀 Understanding biases, noise, errors, variance, and the bias-variance tradeoff in industrial processes is crucial for optimizing performance and ensuring consistent outcomes. ➡️ Bias Definition: Bias in industrial processes refers to consistent deviations from the desired performance due to inherent flaws in design or execution. These deviations are predictable and can lead to persistent inaccuracies. Example: In manufacturing, bias could result from a machine consistently producing parts slightly larger than specifications due to calibration issues. ➡️ Noise Definition: Process noise in industrial settings refers to random fluctuations or variability that affect outcomes unpredictably. It stems from environmental factors, equipment inconsistencies, or human variability. Example: In chemical production, noise may manifest as slight variations in temperature or humidity, impacting product quality inconsistently. ➡️ Errors Definition: Process errors are discrepancies between actual outcomes and intended targets in industrial operations. They encompass biases, variances, and the unpredictable effects of noise. Example: An error in packaging could involve both systematic issues (bias) causing misalignment in labeling and occasional variations (variance) due to equipment malfunction or operator error. ➡️ Variance Definition: Variance in industrial processes measures the extent to which outcomes vary due to changes in operating conditions or execution methods. High variance indicates sensitivity to such changes, leading to inconsistent results. Example: In automotive assembly, variance may arise from differences in assembly line speeds or adjustments in torque settings, affecting the precision of vehicle components. ➡️ Bias-Variance Tradeoff Definition: The bias-variance tradeoff involves balancing systematic errors (bias) against the variability of outcomes (variance). Increasing complexity to reduce bias can raise variance and vice versa. Application: Optimizing a chemical process involves refining parameters to reduce systematic errors without introducing excessive variability that could affect product consistency. Optimal Balance: Achieving a balance ensures processes are robust enough to maintain quality standards while effectively adapting to operational variations. Understanding these concepts in the context of industrial processes empowers teams to diagnose issues accurately, implement targeted improvements, and achieve reliable and efficient operations. #IndustrialEngineering #ProcessOptimization #QualityManagement #BiasVarianceTradeoff #OperationalExcellence #ErrorReduction #ContinuousImprovement #OperationsManagement #QualityControl #BiasVarianceTradeoff #ProcessOptimization #ErrorAnalysis #Biotech #ProcessImprovement #MachineLearning #DataScience #AI #Modeling