作者：文思特咨詢師杜建生
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上一篇我們分享了ASQ推出的《質(zhì)量工具箱第3版（Quality Toolbox 3rd Edition）》中關(guān)于汽車供應(yīng)鏈常用的“控制計(jì)劃”的片段，本文繼續(xù)為您分享：
片段2：數(shù)字時(shí)代的 工業(yè)4.0和質(zhì)量4.0
In the fast-paced world of technology, industries are constantly evolving to meet the demands of the market. One such evolution is the emergence of Industry 4.0, a term that encompasses the integration of digital technologies into manufacturing processes. Quality 4.0, an offshoot of Industry 4.0, focuses on leveraging these technologies to enhance quality control and assurance. This section highlights the concept of Industry 4.0, its impact on quality management and the role of quality professionals, and quality tools that can help professionals in this digital era.
在快節(jié)奏的科技世界中，各行各業(yè)都在不斷發(fā)展以滿足市場(chǎng)需求。其中之一就是工業(yè)4.0的出現(xiàn)，它是一個(gè)將數(shù)字技術(shù)融入制造流程的術(shù)語。質(zhì)量4.0是工業(yè)4.0的一個(gè)分支，其重點(diǎn)是利用這些技術(shù)加強(qiáng)質(zhì)量控制和保證。本節(jié)重點(diǎn)介紹工業(yè)4.0的概念、其對(duì)質(zhì)量管理的影響和質(zhì)量專業(yè)人員的作用，以及可在這個(gè)數(shù)字化時(shí)代幫助專業(yè)人員的質(zhì)量工具。
Industry 4.0
工業(yè)4.0
Industry 4.0, also known as the “Fourth Industrial Revolution,” represents a paradigm shift in manufacturing and production. It involves the integration of various advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), big data analytics, cloud computing, and robotics. These technologies enable automation, real-time data analysis, and connectivity between machines, products, and humans. The primary goal of Industry 4.0 is to create smart factories that are highly efficient, flexible, and capable of autonomous decision-making.
工業(yè)4.0，又稱“第四次工業(yè)革命”，代表著制造和生產(chǎn)模式的轉(zhuǎn)變。它涉及各種先進(jìn)技術(shù)的整合，如物聯(lián)網(wǎng)（IoT）、人工智能（AI）、大數(shù)據(jù)分析、云計(jì)算和機(jī)器人技術(shù)。這些技術(shù)實(shí)現(xiàn)了自動(dòng)化、實(shí)時(shí)數(shù)據(jù)分析以及機(jī)器、產(chǎn)品和人類之間的連接。工業(yè) 4.0 的主要目標(biāo)是創(chuàng)建高效、靈活、能夠自主決策的智能工廠。
Quality 4.0
質(zhì)量4.0
Quality 4.0 builds upon the foundation of Industry 4.0 by incorporating quality management principles and practices into the digital transformation of manufacturing. It aims to leverage digital technologies to improve quality control and assurance processes, enhance product traceability, and enable predictive maintenance. Quality 4.0 emphasizes the use of real-time data analytics, machine learning, and advanced analytics to detect and prevent defects, reduce variability, and optimize production processes. By embracing Quality 4.0, organizations can achieve higher levels of product quality, customer satisfaction, and operational efficiency.
質(zhì)量4.0建立在工業(yè)4.0的基礎(chǔ)之上，將質(zhì)量管理原則和實(shí)踐融入到制造業(yè)的數(shù)字化轉(zhuǎn)型中。它旨在利用數(shù)字技術(shù)改進(jìn)質(zhì)量控制和保證流程，提高產(chǎn)品可追溯性，并實(shí)現(xiàn)預(yù)測(cè)性維護(hù)。質(zhì)量4.0強(qiáng)調(diào)使用實(shí)時(shí)數(shù)據(jù)分析、機(jī)器學(xué)習(xí)和高級(jí)分析來檢測(cè)和預(yù)防缺陷、降低變異和優(yōu)化生產(chǎn)流程。通過采用質(zhì)量4.0，企業(yè)可以實(shí)現(xiàn)更高水平的產(chǎn)品質(zhì)量、客戶滿意度和運(yùn)營(yíng)效率。
Empowering Quality Professionals
增強(qiáng)質(zhì)量專業(yè)技能
Quality professionals play a crucial role in ensuring that products and services meet the desired standards and quality excellence. In the era of Industry 4.0 and Quality 4.0, their roles become even more critical and transformative as they help organizations thrive in disruption. Here are some key ways in which Industry 4.0 empowers quality professionals.
質(zhì)量專業(yè)人員在確保產(chǎn)品和服務(wù)達(dá)到預(yù)期標(biāo)準(zhǔn)和卓越質(zhì)量方面發(fā)揮著至關(guān)重要的作用。在工業(yè)4.0和質(zhì)量4.0時(shí)代，他們的作用變得更加關(guān)鍵和具有變革性，因?yàn)樗麄儙椭M織在混亂中茁壯成長(zhǎng)。以下是工業(yè)4.0增強(qiáng)質(zhì)量專業(yè)能力的一些主要方式。
1. Real-time Monitoring and Control
1. 實(shí)時(shí)監(jiān)視和控制
Industry 4.0 technologies enable quality professionals to monitor and control production processes in real time. Through connected sensors and IoT devices, they can gather data on various parameters such as temperature, pressure, humidity, and machine performance. These data provide valuable insights into process variations, potential defects, and deviations from quality standards. Quality professionals can take immediate corrective actions, minimizing the risk of quality issues and ensuring consistent product quality.
工業(yè)4.0技術(shù)使質(zhì)量專業(yè)人員能夠?qū)崟r(shí)監(jiān)控生產(chǎn)流程。通過連接的傳感器和物聯(lián)網(wǎng)設(shè)備，他們可以收集溫度、壓力、濕度和機(jī)器性能等各種參數(shù)的數(shù)據(jù)。這些數(shù)據(jù)為了解流程變差、潛在缺陷和質(zhì)量標(biāo)準(zhǔn)偏差提供了寶貴的信息。質(zhì)量專業(yè)人員可以立即采取糾正措施，最大限度地降低質(zhì)量問題的風(fēng)險(xiǎn)，確保產(chǎn)品質(zhì)量的一致性。
2. Predictive Analytics
2. 預(yù)測(cè)分析
With the advent of big data analytics and machine learning algorithms, quality professionals can now predict quality issues before they occur. By analyzing historical data and identifying patterns, they can forecast potential defects , equipment failures , and deviations in process parameters. This proactive approach allows for preventive maintenance, early defect detection, and better resource allocation, leading to improved quality outcomes and reduced downtime.
隨著大數(shù)據(jù)分析和機(jī)器學(xué)習(xí)算法的出現(xiàn)，質(zhì)量專業(yè)人員現(xiàn)在可以在質(zhì)量問題發(fā)生之前進(jìn)行預(yù)測(cè)。通過分析歷史數(shù)據(jù)和識(shí)別模式，他們可以預(yù)測(cè)潛在的缺陷、設(shè)備故障和工藝參數(shù)偏差。這種積極主動(dòng)的方法可以實(shí)現(xiàn)預(yù)防性維護(hù)、早期缺陷檢測(cè)和更好的資源分配，從而提高質(zhì)量成果并減少停機(jī)時(shí)間。
3. Enhanced Product Traceability
3. 增強(qiáng)產(chǎn)品可追溯性
Quality 4.0 enables end-to-end product traceability throughout the supply chain. Through technologies like radio frequency identification (RFID) tags and barcode scanning, quality professionals can track the movement of raw materials, components, and finished products. This traceability ensures accountability, facilitates faster recalls in case of quality issues, and strengthens compliance with regulatory standards. Quality professionals can leverage these data to investigate quality incidents, identify root causes, and implement corrective actions.
質(zhì)量4.0實(shí)現(xiàn)了整個(gè)供應(yīng)鏈中端到端的產(chǎn)品可追溯性。通過射頻識(shí)別（RFID）標(biāo)簽和條形碼掃描等技術(shù)，質(zhì)量專業(yè)人員可以跟蹤原材料、部件和成品的移動(dòng)。這種可追溯性確保了產(chǎn)品責(zé)任，有助于在出現(xiàn)質(zhì)量問題時(shí)更快地召回產(chǎn)品，并加強(qiáng)對(duì)監(jiān)管標(biāo)準(zhǔn)的合規(guī)性。質(zhì)量專業(yè)人員可以利用這些數(shù)據(jù)調(diào)查質(zhì)量事故，找出根本原因，并實(shí)施糾正措施。
4. Integration of Quality Systems
4. 質(zhì)量體系整合
Industry 4.0 encourages the integration of quality management systems with other enterprise systems such as enterprise resource planning (ERP) and manufacturing execution systems (MES). This integration allows quality professionals to access real-time data from multiple sources, enabling a holistic view of quality performance across the organization. It facilitates seamless communication, collaboration, and decision-making, leading to streamlined quality processes and faster response times.
工業(yè) 4.0 鼓勵(lì)將質(zhì)量管理體系與企業(yè)資源規(guī)劃 (ERP) 和制造執(zhí)行系統(tǒng) (MES) 等其他企業(yè)系統(tǒng)進(jìn)行整合集成。這種集成使質(zhì)量專業(yè)人員能夠訪問來自多個(gè)來源的實(shí)時(shí)數(shù)據(jù)，從而全面了解整個(gè)組織的質(zhì)量績(jī)效。它促進(jìn)了無縫溝通、協(xié)作和決策，從而簡(jiǎn)化了質(zhì)量流程，加快了響應(yīng)速度。
Quality 4.0 Tools
質(zhì)量4.0工具
While definitive Quality 4.0 tools have yet to be recognized, most industry leaders agree that there is a shortage of appropriate tools to support Quality 4.0 initiatives.
雖然明確的質(zhì)量4.0工具尚未得到認(rèn)可，但大多數(shù)行業(yè)領(lǐng)導(dǎo)者都認(rèn)為，目前缺乏支持質(zhì)量 4.0 計(jì)劃的適當(dāng)工具。
Nicole Radziwill, a pioneer in Quality 4.0 and author of Connected, Intelligent, Automated, identifies an ecosystem of Quality 4.0 tools that can help map business drivers to potential solutions in evaluating business needs (Figure 2.6):
質(zhì)量4.0 的先驅(qū)、《互聯(lián)、智能、自動(dòng)化》一書的作者 Nicole Radziwill 指出，質(zhì)量 4.0 工具的生態(tài)系統(tǒng)有助于在評(píng)估業(yè)務(wù)需求時(shí)將業(yè)務(wù)驅(qū)動(dòng)因素與潛在解決方案聯(lián)系起來（圖 2.6）：
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Artificial intelligence 人工智能 |
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Deep learning 深層學(xué)習(xí)算法 |
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Big data 大數(shù)據(jù) |
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Enabling technologies 輔助技術(shù) |
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Blockchain 區(qū)塊鏈 |
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Data science 數(shù)據(jù)科學(xué) |
Figure 2.6 Relationships among AI, ML, and infrastructure elements.
圖2.6 人工智能、機(jī)器學(xué)習(xí)和基礎(chǔ)設(shè)施要素之間的關(guān)系
(Source: N. M. Radziwill; Connected, Intelligent, Automated (Quality Press, Milwaukee, WI; 2020), p. 53)./《引自質(zhì)量進(jìn)展》雜志
Although machine learning (ML) and continuous improvement are analogous, ML adds intelligence and automation to continuous improvement but cannot replace it.
雖然機(jī)器學(xué)習(xí)（ML）和持續(xù)改進(jìn)有相似之處，但ML增加了持續(xù)改進(jìn)的智能化和自動(dòng)化，而不能取而代之。
The 8D reporting tool covered in Chapter 3 is one such tool. While not exclusively a 4.0 tool, the 8D methodology is a potent problem-solving and communication instrument, particularly in customer complaint scenarios.
第3章介紹的8D報(bào)告工具就是這樣一種工具。雖然8D方法不完全是4.0工具，但它是一種有效的問題解決和溝通工具，尤其是在客戶投訴的情況下。
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