How to Optimize Manufacturing Processes for Quality

Actual picture of me mentoring an apprentice at our #swisslathe shop that Process Capability is more important than just cycle time 📊👈✅ #DrNo At most machine shops, there is a common temptation to prioritize speed and cycle time as indicators of productivity and efficiency. Focusing solely on how fast a part can be made often overlooks a more critical factor --> process capability. Process capability measures the ability of a machining process to consistently produce parts within specified tolerances. We quantify it using statistical metrics like Cpk (process capability index), which assesses how well the process stays centered and within tolerance limits over time. High process capability means fewer defects, greater reliability, and less waste Especially for those of us who strive for "lights out" machining... ...a capable process allows manufacturers to confidently run machines unattended -- productivity without sacrificing quality! Sometimes as a result of studying CpK, we actually machine parts SLOWER, yet our total output ends up being HIGHER than when we were running the parts at a faster cycle time. Why? Because running at the right feeds - speeds - depth of cut - etc parameters at "the sweet spot" and the the higher CpK -- means far less rejects/scrap and also usually longer tool life too! Being able to statistically prove your process will only generate 2-3 reject parts in a million... ...plus tool wear that is super predicatble and stable, often needing no adjustments and longer life for less downtime... --> means you can confidently run production unattended and get closer to the theoretical 168 hrs a week possible machine capacity. When you are able to run a machine close to 168hrs per week, you can outperform another shop with 3x the machines only running on day shift! Not to mention when you amortize your overhead and other fixed cost that don't change (your building lease doesn't care if you operate 40hrs or 168hrs!) then your cost basis goes waaaay down too, making you more competitive. Do you measure Process Capability in your company? What methods do you use to study and measure efficiency? What is your actual machine operating time vs the 168hr theoretical? #manufacturing #machining #machineshop #process #quality #qualitycontrol #cnc #automation

Total Productive Maintenance (TPM) is a comprehensive approach to equipment maintenance that aims to achieve perfect production: zero breakdowns, zero defects, and zero accidents. It integrates maintenance into the daily operations of all employees, from operators to managers, to maximize equipment effectiveness and promote a culture of ownership. The Pillars of TPM: TPM is built on 8 pillars, each focused on proactive and preventive maintenance to enhance operational efficiency: Autonomous Maintenance (Jishu Hozen): Operators take ownership of routine maintenance (cleaning, inspection, lubrication). Empowers operators and reduces dependency on maintenance teams. Planned Maintenance: Scheduled preventive maintenance based on failure data and lifecycle analysis. Reduces unplanned downtime and extends equipment life. Quality Maintenance: Uses root cause analysis and preventive tools to eliminate defects caused by equipment. Focuses on maintaining conditions that assure quality output. Focused Improvement (Kobetsu Kaizen): Cross-functional teams tackle chronic problems and inefficiencies through structured problem-solving. Drives small, incremental improvements in performance. Early Equipment Management: Involves maintenance and production input during equipment design or procurement to improve maintainability, safety, and ease of operation. Education and Training: Develops skills across all levels to ensure correct operation, maintenance, and continuous improvement knowledge. Safety, Health, and Environment: Ensures machines and processes are safe and environmentally friendly. Aims for a zero-accident workplace. TPM in Administrative Functions: Applies TPM principles to office and support areas, optimizing workflows, information flow and efficiency. Benefits of TPM: Fewer breakdowns and unplanned stoppages Higher equipment uptime and productivity Improved product quality Reduced safety incidents Increased employee engagement and accountability Lower total maintenance costs Real-World Example: Context: A bottling plant suffered from frequent filler machine breakdowns, causing lost time and overworked maintenance teams. TPM Applied: Operators were trained to clean and inspect the machine daily (Autonomous Maintenance). Maintenance scheduled a monthly deep inspection (Planned Maintenance). The cross-functional team did a root cause analysis of breakdowns (Focused Improvement). Operator logs and visual indicators were introduced (Education/Training). Result: Breakdowns dropped by 70%, and the plant’s OEE rose from 65% to 85% within six months.

Unlocking Product Quality in Manufacturing: The FMEA Advantage In my experience, one of the most effective ways to enhance product quality in manufacturing is through the diligent application of Failure Mode and Effects Analysis (FMEA). This systematic approach, which I've implemented in various projects, allows us to anticipate potential failures and address them before they occur. FMEA, at its core, is about identifying where and how a process might fail and understanding the impact of different types of failures. It’s a proactive tool, unlike many traditional quality control methods that are reactive. By analyzing processes, materials, and components, FMEA helps in pinpointing weaknesses and provides a structured way to mitigate risks. The beauty of FMEA lies in its versatility. It can be applied to any stage of the manufacturing process, from design to production, and even in post-production analysis. It encourages a mindset of continuous improvement and fosters a culture where quality is a priority. Here’s how FMEA can be transformative: 1. Risk Identification: It helps in early detection of potential failure points. 2. Prioritization: By assessing the severity, occurrence, and detectability of risks, it assists in prioritizing which issues to tackle first. 3. Action Plans: FMEA leads to the development of specific action plans to either eliminate or reduce the risks. 4. Cross-Functional Collaboration: It brings together different departments, enhancing teamwork and shared understanding of quality. Incorporating FMEA into your quality assurance practices doesn’t just improve the product... it also instills a deeper sense of responsibility and quality consciousness among team members. It’s a win-win for both the product and the people behind it. "Quality is not an act, it is a habit." – Aristotle This timeless quote by Aristotle perfectly encapsulates the essence of FMEA in manufacturing. It's about building a habit of excellence and preemptive action. #QualityAssurance #ManufacturingExcellence #FMEA #ContinuousImprovement #OperationalExcellence How has FMEA transformed your approach to product quality? I’d love to hear about your experiences and insights on this topic.

Stop wasting money on Quality Control... ..and start investing in Quality Assurance instead! I recognize that starting with end of the line checks is a natural first step when there are no controls or processes in place. However ↳ QC is like treating symptoms, not the disease. ↳ It catches defects AFTER they've occurred. ↳ You are paying for mistakes, not preventing them. Quality Assurance is what you need. Here's why: → It prevents defects before they happen. → It saves money in the long run. → It boosts customer satisfaction. How to start? Step 1: Map your current process ↳ Identify critical points where defects occur Step 2: Implement in-process checks ↳ Add measurement and verification steps at key points Step 3: Train operators on quality standards ↳ Empower your team to catch issues early Step 4: Use statistical process control (SPC) ↳ Monitor process performance in real-time Step 5: Establish feedback loops ↳ Use data to continuously improve your process Don't let outdated practices hold you back. Shift from reactive to proactive quality management! **** Follow me Angad S. for more!

Stop being so traditional Embrace innovation One way is to stop the bad habit of batch production. ___ Batch Production is a manufacturing method items are produced in batches, before moving on to the next step. Some manufacturers think that larger batches are better because they minimize changeovers. But the truth is the exact opposite! excessively long runs cause overproduction. Operators lose focus working on large batches, while equipment drifts out of standards between changeovers. Worse, they making too much of the wrong product and not enough of the right. There are several drawbacks: +defects are tougher to detect +lots of WIP inventory +space management +uneven workflow +over production +long lead times Switching to One-Piece Flow reduces all these issues. Workcells are arranged so that products can flow one at a time through each process step. Changeovers are more frequent, but shorter. Advantages: +low work-in-process inventory +Responsive to customer demand +Quality defects are detected easily +efficient use of space and material handling The choice between batch and one-piece flow is a no brainer. If you want improvements to quality, productivity, and lead time , choose One-Piece Flow.

Have you ever tried to 'optimize' a machining operation based on 'machinability' data? How useful were these generic 'feeds and speeds'? One of the first lessons I learned as a young machinability consultant and engineer at TechSolve in Cinncinati OH was that optimal process paramters (tool material, geometry, coating, feeds, speeds, coolant, etc.) depend strongly on the specifics of a given operation, including workpiece material, geometry, and the cost structure of the specific job. Most importantly, I also quickly learned that the primary purpose of a machining process is to generate reliable and maximal profit. Therefore, an optimum process is one that is as robust and repeatable as possible, providing 'in spec' parts at the maximum profitability and throughput. The goal of machinability studies should be to generate necessary relationships and data, most importantly progressive tool-wear as a function of cutting time and the impact of tool-wear and feeds/speeds on product quality (dimensions, surface integrity, etc.). We need this information and its variability to model wear progression and the onset of unacceptable workpiece quality for data-driven process optimization. When optimizing, we are not simply trying to maximize metal removal rate and push tool-life to its maximum extent, but our optimization has to be constrained by the statistical variability of tool-wear and associated workpiece quality. While machinability standards such as ISO 8688-2:1989 or controlled/locked aerospace procedures suggest arbitrary end of tool-life criteria such as 0.3 mm maximum flank wear (~0.012"), the end-of-life criterion should always be intelligently defined based on workpiece quality; It does not matter that the tool can keep on cutting when we cannot sell the resulting workpiece and thus generate a profit. I have found that experienced machinists and engineers inherently know this and will consequently limit tool-life to relatively low values to avoid scrapping the workpiece. This practice makes a lot of sense, especially when detailed tool-wear and associated workpiece quality data are not available. Nevertheless, the benefits of even basic tool-wear analysis and quality-constrained process paramter optimization can be substantial. With relatively limited effort, profitability and throughput can often be improved anywhere from 20% for well estbalished (reasoanbly pre-optimized) processes and I have personally helped implement improvements as high as 20x greater process performance in particularly difficult-to-machine alloys and complex operations. The ROI for data-driven optimization depends on the cost metrics of each operation, but can be quite substantial in many cases. I personally feel that we should teach this advanced approach more broadly, particularly to experienced machinists and engineers, as well as the next generation of young professionals entering the field. Figure credit: https://lnkd.in/e5qQrtYM