As a seasoned process technician who has spent many years working in the spinning workshop, I am more than willing to share this journey from "process technician" to "process expert". This is not an easy process; it is a combination of sweat, thinking, setbacks, and breakthroughs. The core idea is: to become a spinning process expert, it is not simply about "knowing" the process, but about deeply "understanding" the interaction between fibers, machines, the environment, and market demands, and having the ability to "anticipate", "solve", and "innovate" complex problems. Here are the key paths I have summarized based on my personal experience: 1. Grounding in the site: From "paper talk" to "getting your hands dirty" (the initial accumulation period): When I first started, I spent a lot of time in the workshop, not just casually observing, but closely monitoring the machines, touching the fibers, inspecting the yarn defects, and measuring the data. I learned practical operations by following the weavers, maintenance workers, and testers, understanding the "temperament" (variations in status) of each machine, experiencing the subtle differences in feel, spinnability, and other properties of different raw materials (cotton, synthetic fibers, blends), and witnessing the immediate and delayed effects of adjusting process parameters (such as spacing, speed, stretch ratio, twist). Key points: Establishing perceptual cognition: Learn to judge the maturity of fibers and the short fiber rate by touch; use your eyes to inspect the hairiness and evenness of the yarn; listen to the abnormal sounds of the equipment. These sensory experiences are valuable supplements to instrument data. Understanding "man-machine-material-process-environment-control": Process is not isolated. The operating habits of the weavers, the wear and tear of the equipment, the fluctuations in raw material batches, and changes in temperature and humidity all affect the process results. Experts need to understand this systematic nature. Accumulating a "fault-phenomenon-causation" database: Yarn defects (such as rough spots, details, cotton knots, foreign fibers), soaring breakage rates, deterioration of the yarn texture... Each anomaly is a learning opportunity. Dig deep to find the root cause (is it the process? The equipment? The raw materials? Or the operation?) .
2. Data-driven: Transition from "empiricism" to "quantitative analysis" (capability improvement period): As I became more familiar with the site, I began to be obsessed with data. Not only did I focus on the final USTER report data of the yarn, but I also paid close attention to the key process indicators throughout the entire process: the cotton yield rate of the cleaning and combing unit, the growth rate of short fibers; the cotton yield rate and yarn quality of the combing process; the weight unevenness rate of the plodder, the CV of the yarn fineness; the tension and elongation rate of the coarse yarn; the breakage rate and CV of twist of the fine yarn; the ten-thousand-meter yarn defect rate and the increase in hairiness of the winding process, etc. Key point: Establish data sensitivity: When seeing a set of data, be able to quickly determine if it is abnormal and whether the fluctuation range is acceptable. Understand the correlation between various indicators (for example, how the change in the cotton yield rate of the combing process will affect the subsequent processes and the yarn strength?) . Master statistical analysis tools: Proficiently use Excel for basic statistical analysis (mean, standard deviation, CPK, correlation analysis), and even learn more advanced tools such as SPC and Minitab. From a large amount of data, identify patterns, trends, and abnormal points. Data traceability: When data is abnormal, be able to quickly locate the specific machine, specific shift, and specific raw material batch. Combine with on-site observations for verification.
3. Profound understanding of principles: From "knowing what it is" to "knowing why it is so" (the period of theoretical elevation)
Experience: When the on-site experience and data accumulation reach a certain level, a bottleneck will be encountered. At this point, systematically delving into the learning of spinning principles, fiber physics, mechanical principles, and quality control theories becomes extremely crucial. I re-read classic textbooks (such as "Spinning" and "Cotton Spinning Handbook"), attended industry technical lectures, and conducted in-depth research on the technical materials of well-known equipment manufacturers. Key points: Mastering "why": Why is this gap range reasonable? Why does this kind of fiber require a higher twist? How does the stretch distribution affect the straightness and parallelism of the fibers? How does the twist triangle zone affect fuzz and strength? Understanding these underlying physical and mechanical principles is necessary to break away from reliance on "experience values" and carry out innovative work supported by theory. Understanding equipment limitations: The implementation of the process depends on the equipment. In-depth understanding of the structural characteristics of each model, the performance limitations of key components (such as roller accuracy, rubber roller hardness, steel collar wire loop matching, electronic weft detector sensitivity), is necessary to optimize the process design and propose effective equipment renovation suggestions when designing the process. Raw material characteristics are the core: Become an "expert" in fiber properties. Different origins, varieties, processing methods of cotton, different specifications, cross-sections, surface treatments of synthetic fibers, their length, fineness, strength, maturity, moisture regain, friction coefficient, crimp degree and other properties vary greatly, directly affecting the design of process parameters such as loosening, combing, stretching, and twisting. Experts must be able to "tailor" the process according to the raw materials.