In the workshop, the equipment is constantly roaring and the workers are busy, which seems to be
a busy scene. However, the production schedule on the extension of the red letter alarming, the
warehouse piles of semi-finished products silent accusations of flow stagnation, quality inspection link
frequently lit red light is devouring the profits - the surface of the busy, often masking the deep-seated
efficiency of the black hole. In the dramatic increase in cost pressures, customer demand, competition is
increasingly hot today, enhance the efficiency of the manufacturing process is not the icing on the cake,
but the lifeblood of the survival of enterprises.
Traditional efficiency dilemma: visible waste and invisible bottlenecks
Once upon a time, efficiency improvement relied mainly on the on-site improvement of lean production and
the introduction of automated equipment. However, in the face of the complex and changing market environment,
the traditional means are becoming weak:
“Black box” production, lagging decision-making: Equipment status, work-in-process location, and production
progress rely on manual recording and reporting, with information lagging behind and prone to distortion. Managers
are like “blind men feeling an elephant”, difficult to control the overall situation in real time, and even more unable
to quickly respond to abnormalities.
Rigid planning, scheduling inefficiency: Static production planning in the face of equipment failure, material
shortages, order insertion and other emergencies can not do anything. Dispatchers are tired of “fire-fighting”,
decision-making based on experience, resulting in idle equipment and production congestion coexist, the overall
capacity can not be effectively released.
Quality fluctuation, cost surges: quality relies on after-the-fact sampling, problem discovery lags, rework and scrap
costs are high. Lack of data support for the adjustment of process parameters makes it difficult to steadily improve
the yield rate, and the hidden quality cost eats into the profit.
Silos, difficult to collaborate: equipment, MES, ERP, warehousing and other systems work separately, data can not be
interconnected. Production, planning, materials, quality and other departments of information fragmentation,
inefficient collaboration, serious internal conflict.
Digital empowerment: unlocking new dimensions of manufacturing
process efficiency
The deep integration of digital technology is opening up a new path for manufacturing process efficiency improvement,
the core of which lies in data-driven transparency, intelligence and self-optimization:
Full-area sensing, transparency and visibility:
Equipment interconnection: Industrial Internet of Things (IIoT) technology allows every piece of equipment and sensor to
become a data source, collecting real-time information on equipment status (vibration, temperature, current), production
parameters, and energy consumption.
Material Tracking: Accurately track the flow trajectory and status of raw materials, work-in-progress, and finished products
through barcode, RFID, or visual identification to realize transparent management of the entire process.
Digital Twin: Build a virtual mirror of the physical workshop, mapping the production status in real time, allowing managers
to “see the whole factory at a glance” and quickly locate bottlenecks and abnormalities.
Intelligent decision-making and precise execution:
Dynamic scheduling (APS): Based on real-time equipment status, material inventory, order priority, process constraints and
other multi-dimensional data, intelligent algorithms automatically generate the optimal dynamic scheduling plan, quickly
respond to changes, maximize equipment utilization and order delivery rate.
Predictive Maintenance: Analyze equipment operation data, predict potential failures, change passive maintenance to active
maintenance, significantly reduce unplanned downtime, and ensure production continuity.
Real-time scheduling and optimization: AI engine dynamically adjusts work order allocation and equipment parameters
according to the real-time conditions of the production line (e.g., fluctuations in equipment efficiency, backlogs in work
processes), realizing self-balancing and self-optimization of production line efficiency.
Closed-loop control, quality and efficiency can be increased:
Online quality monitoring: machine vision, spectral analysis and other technologies to achieve full inspection or
high-frequency sampling, milliseconds to identify defects, real-time alarms and automatic interception of defective
products to avoid batch losses.
Process Parameter Optimization: Using big data to analyze historical production data to find out the key process parameter
combinations that affect quality and efficiency, and continuously optimize them to steadily improve yield rate and production beat.
Quality Tracing and Root Cause Analysis: Open up the whole production process data, realize minute-level accurate tracing
of quality problems, quickly locate the root cause and promote effective improvement.
Seamless collaboration to break down silos:
Data Integration Platform: Build a unified data platform or centralized platform to integrate data from equipment level,
execution level (MES), management level (ERP/PLM) and supply chain system to break information barriers.
Cross-departmental collaboration: Based on real-time shared data, planning, production, materials, quality and other
departments work closely together to achieve efficient matching of demand, supply and production, reducing waiting
and waste.
Pragmatic Advancement: The Way to Improve Efficiency on the Ground
Efficiency revolution is not a one-day effort, and requires strategic determination and solid action:
Pain Point Entry, Value Oriented: Analyze the bottlenecks of your own efficiency (e.g. low OEE of equipment, long time of
line change, high inventory of WIP, high fluctuation of quality), choose 1-2 high-value pain point scenarios (e.g. predictive
maintenance, intelligent scheduling, online quality inspection) to prioritize breakthroughs, and get quick results to build
up your confidence.
Data foundation, connectivity first: Ensure that key equipment data can be collected and transmitted. Build a stable and
reliable industrial network (wired/wireless), deploy edge computing to handle data with high real-time requirements, and
lay a good foundation for intelligent applications.
Platform support, ability precipitation: Adopt modular and scalable industrial Internet platform or manufacturing operation
management (MOM) system to realize data aggregation, governance, analysis and application development, avoiding the
formation of new “chimneys”.
Lean-based, digital empowerment: Digital technology is a tool, not an end in itself. Strengthen the foundation of lean
management (e.g., 5S, standardized operation) and integrate digital tools into the lean improvement process to maximize
effectiveness.
Organizational adaptation and talent upgrading: Promote process reengineering and break down departmental walls.
Cultivate composite talents who understand both production process and data thinking, enhance the digital literacy of
all staff, and create a culture of continuous improvement.
Efficiency is Competitiveness: The Cornerstone of Future Intelligent Manufacturing
Enhancing the efficiency of the manufacturing process has significance far beyond cost savings. It is the foundation for
enterprises to respond to market speed, guarantee delivery capability, improve product quality and realize flexible
manufacturing. Under the wave of digitization, the connotation of efficiency is being redefined - from local optimization to
global intelligence, from experience-driven to data-driven, and from reactive response to active prediction.
Those enterprises that take the lead in transforming data into insights, insights into actions, and actions into efficiency
advantages will gain unrivaled initiative in the fierce market competition. The leap in manufacturing process efficiency is not
only a refinement of factory operations, but also a strategic pivot for enterprises to face the future and build core competitiveness.
Embracing this data-driven efficiency revolution is an inevitable choice for the manufacturing industry to move towards
high-quality development.