Quality Digest Defines Enhanced Webinar Events

For twenty years as an editorial contributor to Quality Digest magazine, I have had the pleasure of authoring or collaborating more than 80 articles for the publication. During this two-decade tenure, I have worked with Dirk Dusharme (pictured left), Editor in Chief of Quality Digest.

Quality Digest’s website receives more than three million page views each year, which provide editorial content, live broadcasts, videos, and on-demand webinars presented by industry experts on international quality standards, leadership, manufacturing, metrology, statistical process control, training, and more.

Quality Digest continues its important role as companies navigate a post-COVID reality with a critical role of safety, quality, efficiency, and resiliency. Quality elements are no longer an after-thought.  It is essential when examining automation, lean manufacturing, and new paradigms for best practice.  During COVID, all of us became more remote savvy and the demand for visionary content and information essential.

According to Dusharme, “Since their debut almost a decade ago, Quality Digest's "enhanced" webinar events have raised the bar for the traditional webinar experience. Our audience has come to expect concise, informative, and engaging presentations with subject matter experts who know what they are talking about. Apart from the traditional quality topics, we delve into areas that broaden our audience’s knowledge. These topics range from cybersecurity, to supply chain management, to understanding and dealing with cognitive biases. Our goal is to provide up-to-date, actionable information that our audience can immediately put to use. Live video feeds of the presenters and the products, interactive Q&A sessions, surveys, and valuable downloads all make up our usual webinar experience, followed by next-day access to the on-demand recording and materials.”

Enhanced Webinars from Quality Digest feature real-time streaming video of host, subject matter expert, and a case study in action.  Users can email questions, chat, or download files in real-time.  This modality is ideal for visual case studies/product demos, team or customer training, and new product/new service announcements.


Upcoming Enhanced Webinars from Quality Digest:
Quality Management Automation in SMB:
Real World Best Practices, Lessons Learned

Register for the May 25, 2021 webinar at 11:00 AM Pacific Time (US and Canada) here.
 
Small- and medium-sized organizations face unique challenges when it comes to automating quality processes. Whether an SMB or independent subsidiary, many lack the resources, manpower and budget that larger organizations enjoy. SMBs must know when and what to automate. More importantly, they need to identify bandwidth constraints.

Crystal Sliva, Quality Assurance Systems Administrator, Whitehouse Intertek will discuss her experience in addressing the unique quality challenges faced by small and medium organizations. She will be joined by David Isaacson, Senior Director Product Marketing ETQ.

Attendees will learn:
  • How to address the unique quality process challenges of small and medium organizations
  • How to evaluate the hidden costs of paper and manual processing
  • When and what processes to automate
  • Lessons learned and best practices from an SMB that has automated quality processes

The Quality Journey:
How to Move from Foundations to Operational Excellence

 
Register for the June 8 webinar at 11:00 AM Pacific Time (US and Canada) here.

Every organization wants to provide innovative products and services that meet customer requirements and support the business strategy. Yet there is no single approach to achieving this. While zero defects and customer delight are reasonable goals every leader wants to achieve, there are many different ways to get there.

In the webinar The Quality Journey: How to Move from Foundations to Operational Excellence, Nicky Jaine, Quality Director and continuous improvement leader at Intelex Technologies, ULC, will show how an effective quality practice develops over time and grows to meet the needs of the organization. Attendees will learn the following:
  • How quality principles can support operational excellence.
  • How to make quality foundational to business strategy.
  • Why certification is not always the only answer.
Keep an eye out for other upcoming Quality Digest webinars.
About The Author
Thomas R. Cutler is the President and CEO of Fort Lauderdale, Florida-based,
TR Cutler, Inc., celebrating its 22nd year. Cutler is the founder of the Manufacturing Media Consortium including more than 8000 journalists, editors, and economists writing about trends in manufacturing, industry, material handling, and process improvement. Cutler authors more than 1000 feature articles annually regarding the manufacturing sector. Nearly 5000 industry leaders follow Cutler on Twitter daily at @ThomasRCutler. Contact Cutler at trcutler@trcutlerinc.com.

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OTHER ARTICLES

Building a Smart Factory is Possible Using Machine Learning

Article | December 7, 2021

Machine learning in manufacturing is becoming more widespread, with businesses like GE, Siemens, Intel, Bosch, NVIDIA, and Microsoft all investing heavily in machine learning-based ways to enhance manufacturing. Machine learning is predicted to expand from $1 billion in 2016 to USD 9 billion by 2022at a compound annual growth rate (CAGR) of 44% throughout the forecast period, according to Markets & Markets. The technology is being utilized to cut labor costs, achieve better transition times, and increase manufacturing speed. “I advocate business leaders get to know more about what AI can do and then leverage AI in proofs of concept.” – Michael Walton, Director and Industry Executive, Microsoft speaking with Media 7 Machine learning can help enhance manufacturing processes at the industrial level. This can be achieved by assessing current manufacturing models and identifying flaws and pain factors. Businesses can rapidly address any difficulties to keep the manufacturing pipeline running smoothly. Let us explore how machine learning is transforming manufacturing operations. How Machine Learning Is Transforming Manufacturing Operations “The greatest benefit of machine learning may ultimately be not what the machines learn but what we learn by teaching them.” - Pedro Domingos Machine learning in manufacturing is revolutionizing manufacturing operations and making them more advanced and result-oriented, so let's have a look at how this is unfolding. Allows for Predictive Maintenance Machine learning provides predictive maintenance by forecasting equipment breakdowns and eliminating wasteful downtime. Manufacturers spend far too much time correcting problems instead of planning upkeep. In addition to enhancing asset dependability and product quality, machine learning systems can forecast equipment breakdown with 92% accuracy. Machine learning and predictive analytics increased overall equipment efficiency from 65% to 85%. Increases Product Inspection and Quality Control Machine learning is also utilized for product inspection. Automated inspection and supervision using ML-based computer vision algorithms can discriminate between excellent and bad products. These algorithms simply need excellent samples to train; therefore a fault library is not required. However, an algorithm that compares samples to the most common errors can be built. Machine learning reduces visual quality control costs in manufacturing. Forbe's says AI-powered quality testing can boost detection rates by up to 80%. Logistics-related Tasks Are Automated To run a production line, industrial companies need considerable logistics skills. The use of machine learning-based solutions can improve logistics efficiency and save expenses. Manual, time-consuming operations like logistics and production-related documentation cost the average US business $171,340 annually. It saves thousands of manual working hours every year to automate these everyday procedures. Using Deep Mind AI, Google was able to lower its data center cooling bill by 40%. Creates More Business Opportunities Machine learning is frequently used in the production process. Substantial data analysis is required to create new items or improve existing products. Collection and analysis of huge amounts of product data can help find hidden defects and new business opportunities. This can help improve existing product designs and provide new revenue streams for the company. With machine learning, companies can reduce product development risks by making smarter decisions with better insights. Protects Company’s Digital Assets On-premise and cloud-based machine learning systems require networks, data, and technological platforms to function. Machine learning can help secure these systems and data by restricting access to vital digital platforms and information. Humans’ access sensitive data, choose applications, and connect to it using machine learning. This can help secure digital assets by immediately recognizing irregularities and taking appropriate action. Harley Davidson's Sales Climbed by 40% Using Albert – The ML & AI-Powered Robot Today, traditional marketing is harder to break through. It's easy to see why Albert (an AI-powered robot) would be a good fit for Harley Davidson NYC. Thanks to machine learning and artificial intelligence, robots are producing news stories, working in hotels, controlling traffic, and even running McDonald's. Albert works well with social media and email marketing. It analyzed which customers are more likely to convert and modifies the personal creative copies on its own for the next process. Harley-Davidson is the only company to employ Albert in its business. The company evaluated customer data to find prior consumers who made purchases and spent more time browsing the website than normal. Albert used this data to categorize customers and scale up test campaigns. Using Albert, Harley-Davidson's sales climbed by 40% and leads increased 2,930%, with half coming from high-converting ‘lookalikes' detected by AI and machine learning. Final Words The groundbreaking benefits of machine learning are the pillars of machine learning applications in manufacturing. Machine learning in manufacturing helps enhance productivity without compromising quality. According to Forbes, Amazon has automated warehouse logistics picking and packing using a machine learning system. With Kiva's help, Amazon's typical ‘click to ship' time dropped from 60-75 minutes to 15 minutes. So, industry leaders are seeing fantastic outcomes, and machine learning in manufacturing is the future. FAQ How is machine learning used in manufacturing? Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process. Which two forms of machine learning are there? Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data. What is a machine learning model? A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How is machine learning used in manufacturing?", "acceptedAnswer": { "@type": "Answer", "text": "Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process." } },{ "@type": "Question", "name": "Which two forms of machine learning are there?", "acceptedAnswer": { "@type": "Answer", "text": "Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data." } },{ "@type": "Question", "name": "What is a machine learning model?", "acceptedAnswer": { "@type": "Answer", "text": "A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm." } }] }

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Lessons Learned in Electronics Transforms Other Discrete Manufacturing Operations

Article | May 10, 2021

Jason Spera, picture left, recently shared his vantage of the changes for factory floor automation in 2021. Jason is CEO and Co-Founder, Aegis Software. Spera is a leader in MES/MOM software platforms for discrete manufacturers with particular expertise in electronics manufacturing. Founded in 1997, today more than 2,200 factory sites worldwide use some form of Aegis software to improve productivity and quality while meeting regulatory, compliance and traceability challenges. Spera's background as a manufacturing engineer in an electronics manufacturing company and the needs he saw in that role led to the creation of the original software products and continue to inform the vision that drives Aegis solutions, like FactoryLogix. He regularly speaks on topics surrounding factory digitization, IIoT, and Industry 4.0. Contact Jason on LinkedIn.

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What are the Risks that Manufacturing Face in the Current Times?

Article | December 30, 2021

Risk management in manufacturing has always been a top priority for manufacturers to avoid any unfortunate incidents. As a result, it is possible to create a more secure work environment for employees by conducting risk assessments and implementing remedies. “If you don’t invest in risk management, it doesn’t matter what business you’re in, it’s a risky business.” – Gary Cohn, an American Business Leader. As of 2019, the worldwide risk management market was valued at $7.39 billion, and it is expected to rise at a CAGR of 18.7% from 2020 to 2027, according to allied market research. Why is Risk Assessment Critical in Manufacturing? The manufacturing industry must have a credible risk assessment and management plan to defend itself from any breaches. Risk assessment helps firms understand the dangers they face and their implications if their systems are compromised. Hence, risk assessment is very critical in the manufacturing industry. Five Risk Assessment Principles Identify hazards/risks - Employers must examine their workers' health and safety risks. Therefore, an organization must regularly inspect its employee’s physical, mental, chemical, and biological threats. Identify who may be hurt and in what way – Identifying the personnel both full-time and part-time at-risk. Employers must also examine threats to agency and contract personnel, visitors, clients, and other visitors. Assess the risks and act accordingly - Employers must assess the likelihood of each danger causing injury. This will evaluate and lower the chance at the working space. Even with all safeguards, there is always some danger. Therefore, employers must assess if danger is still high, medium, or low risk. Get the Risks Documented - Employers with five or more employees must record the critical findings of the risk assessment in writing. In addition, register any risks identified in the risk assessment and actions to minimize or eliminate risk. This document confirms the evaluation and is used to examine working practices afterward. The risk assessment is a draft. It should be readable. It shouldn't be hidden away. The risk assessment must account for changes in working techniques, new machinery, or higher work objectives. 5 Manufacturing Risks to Consider in 2022 Accidents at Work Even if official safety policies and programs are designed, followed, and enhanced, manufacturers may endure workplace accidents and injuries. Risk assessment for workplace accidents assists in mitigating the negative impact on both employees and the organization. Environmental Mishaps Manufacturers have distinct issues regarding fuel handling and hazardous waste disposal in facilities. Sudden leaks or spills may be extremely costly to clean up and result in fines from state and federal agencies. Risk assessments for such plant accidents assist businesses in mitigating financial losses. Equipment Breakdowns Essential machinery throughout the production process might fail at any time, incurring significant repair or replacement costs. Therefore, it's critical to recognize that business property insurance may not cover mechanical issues. Risk assessment and prepayment solutions protect against equipment failures without interfering with typical company operations. Supply Chain Disruption Dependence on your supply chain may result in unintended consequences that are beyond your control. For example, if you experience downtime on the manufacturing line due to a supplier's failure to supply materials or parts, you risk losing revenue and profitability. If a disturbance to your supply chain poses a hazard, risk management can assist you in managing it more effectively by quickly identifying the risk and providing a suitable response. Operation Temporarily Suspended Depending on the severity of the weather event, a factory might be severely damaged or perhaps utterly wrecked. While major repairs or rebuilding are being undertaken, recouping lost income might be vital to the business's future profitability. Risk assessment in this area enables your organization to budget for overhead expenditures such as rent, payroll, and tax responsibilities during the period of suspension of operations. Final Words Risk management is critical in manufacturing because it enables manufacturers to comprehend and anticipate scenarios and create a well-planned response that avoids unnecessary overhead costs or delays in delivering the production cycle's final result. Manufacturing risks are undoubtedly not limited to the risks listed above and may vary according to the nature of the business and regional environmental conditions. Therefore, create a well-defined strategy to overcome threats in your business and be productive at all times. FAQ How are manufacturing business risks classified? In most cases, the business risk may be categorized into four types: strategic risk, regulatory compliance risks, operational compliance risks, and reputational risks. Why should a manufacturer conduct a risk assessment? Every manufacturing employment has risks for injury or illness. But risk evaluations can significantly minimize workplace injuries and illnesses. In addition, they assist companies in discovering strategies to reduce health and safety risks and enhance knowledge about dangers.

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Corporate Citizenship and Industrial Investment in Uganda: Key to Accessing Significant Affordable Workforce

Article | June 28, 2021

Manufacturing journalist Thomas R. Cutler visited the remarkable and magnificent country of Uganda. Foreign investment is coming into the country and that is a good thing; it is not however, enough. To tap into this workforce corporate citizenship and contribution is essential. Just as I underestimated the stamina needed to climb the mountain to experience the gorillas, the role of transforming Uganda requires a careful, well-thought approach.

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