Konstantin Paradizov’s Post

When operator performance is judged on not fully understood metrics and a factor into that metric is controlled by the operator, expect the operator to be in a protection mode afraid to tell the truth. Truth can be painful when it's honest though the painful realizations are the pathway to positive change.

🔧 Discover the secrets to top-quality manufacturing! Learn how SPC & Yield Optimization can revolutionize your processes. 📈✨ #Manufacturing #QualityControl #Efficiency #ContinuousImprovement 👇

🔧 Mastering SPC and Yield Optimization in Manufacturing 📈 Ever wondered how top manufacturers maintain high quality while slashing waste? The secret sauce: Statistical Process Control (SPC) and Yield Optimization. Let’s dive in and transform your production process! 🔍 What is Statistical Process Control (SPC)? Imagine baking cookies 🍪. You want each batch to be perfectly crispy and delicious. SPC is like a system that continuously checks your baking to ensure consistent quality. SPC Simplified: 1. Data Collection: Gather data during production. 2. Control Charts: Plot data to monitor performance. 3. Analysis: Spot variations or issues. 4. Action: Correct issues early to maintain quality. Benefits of SPC: ・Consistency: Steady quality assurance. ・Efficiency: Early issue detection saves resources. ・Customer Satisfaction: Reliable products delight customers. 🎯 Yield Optimization Explained Yield Optimization maximizes good products while minimizing defects. It’s like squeezing every drop from an orange 🍊. Steps to Yield Optimization: 1. Analyze Processes: Find inefficiencies. 2. Identify Bottlenecks: Locate defects or losses. 3. Implement Changes: Reduce waste and boost good product yield. 4. Monitor and Adjust: Continuously improve. Why Optimize Yield? ・Higher Profits: More good products, less cost. ・Eco-friendly: Less waste, greener production 🌍. ・Competitive Edge: Stand out with higher yields. 🔧 SPC and Yield Optimization: A Powerful Combo Together, SPC and Yield Optimization ensure consistent quality and continuous improvement. SPC maintains control; Yield Optimization enhances efficiency. 📊 Real-World Example: Automotive Industry 🚗 Precision is critical in automotive manufacturing. SPC monitors processes like engine assembly. Yield Optimization boosts flawless engine production, cutting scrap and rework. 🤔 Ready to Optimize? Start with small steps, gather data, and watch your production become a well-oiled machine. Continuous monitoring and improvement are key. Join the discussion! Have you implemented SPC or Yield Optimization? Share your insights below. Let’s learn and grow together! 🌱 #Manufacturing #QualityControl #ProcessImprovement #Efficiency #LeanManufacturing #ContinuousImprovement #DataDriven #Sustainability #CustomerSatisfaction

Virtual Statistics for Quality Control Webinar: Essential Steps and Techniques Used to Quantify Variability in Manufacturing Processes, and to Assure Quality Products: DUBLIN, Nov. 16, 2023 /PRNewswire/ -- The "Statistics for Quality Control" webinar has been added to ResearchAndMarkets.com's offering. This 6-hour virtual seminar is designed to provide a comprehensive overview of techniques and steps used to quantify variability in manufacturing...

We talk a lot about process outputs. We say things like OEE, yield, first-time-pass. We measure things like units produced, in-process reject rates, scrap, rework. But what about those hidden outputs? You know, the stuff that causes “extra” work? And make no mistake, we rationalize these things as extra. Running an RCA is extra… CAPA actions are extra… Audit observations are extra… Nonconformance reports are extra… Deviation approvals are extra… …they’re extra becuase they’re not planned. Here’s the truth: those things are not extra, they’re process outputs. Sure, we don’t want those little gremlins…but they exist! And your process makes them. And like any process output (or gremlins), someone has to manage them. Just like when Production has a record-breaking period and material handlers are struggling to keep up moving all those finished goods, Quality struggles to move all those corrections, deviations, and nonconformance investigations when there’s a poor quality production period. —We’re just way more excited to bust our butts for crushing production targets! And who wouldn’t be? Winning feels good. Setbacks feel bad— But poorly performing processes produce both poor products AND Quality firefighting—not a desirable combo. Sustained poor performance necessitates more Quality resources. …but CAPA and deviation management and audit observations don’t generate revenue…and it’s just “extra” work that will go away when things get better, right? And then we start to rationalize: why increase the number of Quality personnel? Why divert resources? Why not instead focus harder on production, engineering, and maintenance? Hey…maybe even divert Quality personnel to supplement production efforts! Ah, it’s a slippery slope when we think about poor quality as temporary, and worse when we relegate it to something of lesser importance like a paper exercise to satisfy non-value added requirements. This isn’t judgement. Every business needs to assess and respond to their unique circumstances. Being aware, however, of pitfalls and missteps that are all too common—sometimes with irreparable consequences—is the first step in not setting off a chain of unfortunate events. Control your process outputs…especially the undesirable ones!

Why do we even measure things? Some may measure to control product quality, increase yield, and fulfill any relevant regulatory requirements. But I wanted to dig a little deeper, so I asked the same question to a colleague, and he answered with a reflective look, "Ty, honestly, measurement makes it possible for my company to create products that match the design exactly to our specifications and guarantee product quality." I sincerely told him, "How do you ensure you get the right product for internal processes..." He said to me, " Actually, I depend on tribal knowledge. Many of our scales have been purchased and implemented before I worked there." The red flags started to show: product risk, measurement uncertainty, bad batch, underfilling, and overfilling. These issues can occur when the right tools are not offered to our customers. Established in 2007, Good Weighing Practice, our weighing standard, has helped our partners with risk mitigation by evaluating our products to meet our customers' accuracy requirements specific to their applications. With a few fundamental questions. -How do you plan on using our products to fit the needs of their operations? -What are the consequences if your scale is wrong? -What is your process tolerance? -What is your safety factor? As we identify your pain points, we tackle them together using our scientific process(GWP) to match the product to your custom application. The methodology removes the grey area and draws a clear line and where to draw it. At Carlton Scale, we understand that measurements occur at spots we refer to as "critical control points" throughout the manufacturing and quality control process. If these critical points lack the proper weighing devices, you could lose control over the process and have poor-quality finished goods, waste, and failed audits. As your local solution provider with the backing of the biggest globally known metrology distributor Mettler-Toledo International, Inc, we are devoted to creating unique, fit-for-purpose, integrated solutions to help our customers achieve their desired outcomes. 

In today's fiercely competitive landscape, manufacturing companies grapple with soaring competition and escalating raw material costs. While these challenges may seem insurmountable, savvy companies recognize the power of focusing on what they can control: their processes. It's evident that the key to sustainable success lies in continuous improvement across quality, efficiency, and cost reduction fronts. Yet, many companies still rely solely on post-production inspections to identify quality issues. Enter Statistical Process Control (SPC) – a game-changer in the realm of quality management. By shifting from detection-based to prevention-based controls, SPC empowers companies to monitor process performance in real-time. This proactive approach enables operators to identify trends or deviations before they translate into non-conforming products and unnecessary scrap. In essence, SPC doesn't just optimize processes; it revolutionizes quality management paradigms, fostering a culture of foresight and efficiency. #ExellenceWithMohan

From Data to Decisions: Harnessing SPC for Process Optimization. SPC – Statistical process control is the application of statistical methods to monitor, assess, analyze and control the quality of a production/Manufacturing/any other category of critical processes. Statistical Process Control (SPC) is crucial in ensuring product quality and process stability by providing real-time monitoring and analysis. Understanding metrics like Cp and Cpk allows businesses to assess process capability and make informed decisions to improve efficiency and reduce defects. By implementing SPC effectively, organizations can maintain consistent quality, minimize variation, and ultimately enhance customer satisfaction. If you're eager to explore and delve deeper into an 'End-to-End Next Gen eQMS,' reach out to us for expert guidance and tailored solutions to improve your CoQ, reduce the CoPQ and Build a Quality Culture with overall quality management system. Let's navigate the journey to enhanced quality mgmt. together! All the QEHS processes, inbuilt linkages or their automated interactions help organizations to execute the activities on time and effectively in a closed loop way! want to know more? Take a stand, book your complimentary demo on End-to-end eQMS/QEHS now - https://lnkd.in/guQ2DWXS Aditya Chaudhary Palash Chatterjee Ved Prakash Saini Hexagon Manufacturing Intelligence - K A I #qms #eqms #qualitymanagement #digitalsolutions #spc #qualitymanagementsystem