當今世界進入了數(shù)據(jù)爆炸的時代，數(shù)據(jù)成為企業(yè)最重要的資產(chǎn)之一，是實現(xiàn)智能制造的基礎(chǔ)。隨著各類數(shù)據(jù)采集、整理、分析相關(guān)技術(shù)的發(fā)展及應(yīng)用，數(shù)據(jù)的價值逐步在多方面得到了體現(xiàn)，越來越受到企業(yè)的重視。數(shù)據(jù)在制造企業(yè)內(nèi)的核心價值凸顯。
In the field of product design and development, enterprise can through the product definition (MBD) implementation based on the model, build product Digital Twin Twin model (Digital), at the same time of delivery of physical products, the delivery of products Digital Twin, establish data supply chain.
在產(chǎn)品設(shè)計研發(fā)領(lǐng)域，企業(yè)可通過實現(xiàn)基于模型的產(chǎn)品定義（MBD），構(gòu)建產(chǎn)品的Digital Twin（數(shù)字孿生模型），在交付實體產(chǎn)品的同時，交付產(chǎn)品的Digital Twin，建立數(shù)據(jù)供應(yīng)鏈。最大限度地利用已有的設(shè)計成果，實現(xiàn)設(shè)計重用。此外，企業(yè)還可以構(gòu)建自己的三維零件庫，這方面目前市場上已有完整的解決方案，如德國卡迪納斯（CADENAS）。
Make the best use of existing design results and realize design reuse. In addition, companies can build their own three-dimensional parts library, which is now available on the market for complete solutions, such as CADENAS in Germany.
隨著社交媒體的廣泛應(yīng)用，企業(yè)進行產(chǎn)品創(chuàng)新設(shè)計也可以基于社交大數(shù)據(jù)的反饋來優(yōu)化設(shè)計方案，使產(chǎn)品設(shè)計更加貼近客戶的需求。數(shù)據(jù)能夠驅(qū)動現(xiàn)代制造企業(yè)的產(chǎn)品研發(fā)、生產(chǎn)、采購等業(yè)務(wù)流程。例如，可通過結(jié)構(gòu)化數(shù)據(jù)來描述客戶需求，并且與產(chǎn)品數(shù)據(jù)關(guān)聯(lián)起來，將產(chǎn)品結(jié)構(gòu)、裝配關(guān)系、制造工藝、產(chǎn)品配置等產(chǎn)品全生命周期的數(shù)據(jù)統(tǒng)一管理。在整個產(chǎn)品生命周期，從客戶需求到概念設(shè)計、詳細設(shè)計、工藝設(shè)計、仿真試驗、生產(chǎn)制造到售后服務(wù)過程的數(shù)據(jù)應(yīng)當全部貫通，并且通過結(jié)構(gòu)樹的方式準確地表達。這樣，客戶需求如果出現(xiàn)變更，會對產(chǎn)品結(jié)構(gòu)，乃至后續(xù)的制造和服務(wù)產(chǎn)生哪些影響，才能夠追溯清楚。對企業(yè)級BOM的有效管理，是制造企業(yè)實現(xiàn)設(shè)計重用，提升研發(fā)效率，實現(xiàn)產(chǎn)品快速配置的基礎(chǔ)。
In this way, if the customer needs change, the product structure, and even subsequent manufacturing and service, can be traced back clearly. The effective management of enterprise BOM is the basis for manufacturing enterprises to realize design reuse, improve r&d efficiency and realize the rapid configuration of products.
企業(yè)進行工藝規(guī)劃、生產(chǎn)計劃排產(chǎn)和確定物料需求計劃，也可以利用數(shù)據(jù)驅(qū)動。企業(yè)應(yīng)用ERP系統(tǒng)可以實現(xiàn)產(chǎn)、供、銷、人、財、物的協(xié)同管理，MES系統(tǒng)則要處理人、機、料、法、環(huán)等影響生產(chǎn)和質(zhì)量的數(shù)據(jù)。根據(jù)不同產(chǎn)品的銷售數(shù)據(jù)分析，還可以有針對性地調(diào)整產(chǎn)品的生產(chǎn)計劃等等。
The enterprise carries out the process planning, the production plan to produce and determines the material demand plan, also can use the data drive. Enterprise application ERP system can realize the cooperative management of production, supply, sales, people, wealth and things, and the MES system should deal with the data of people, machine, material, law, ring, etc., which affect production and quality. According to the analysis of sales data of different products, the production plan of products can be adjusted accordingly.
除以上提到的以外，在質(zhì)量管理、企業(yè)內(nèi)外部協(xié)同、決策支持、供應(yīng)鏈的分析與優(yōu)化、市場營銷……等領(lǐng)域，數(shù)據(jù)的價值日益凸顯，此外許多新的技術(shù)，如物聯(lián)網(wǎng)的應(yīng)用、增材制造的實現(xiàn)等都需要基于數(shù)據(jù)。這些數(shù)據(jù)有些來自企業(yè)內(nèi)部，如設(shè)計、加工、仿真等產(chǎn)品數(shù)據(jù)，設(shè)備、營銷、生產(chǎn)、采購等運營數(shù)據(jù)；有些來自外部，如客戶、供應(yīng)商等價值鏈數(shù)據(jù)，以及社交媒體數(shù)據(jù)等等。越來越多的制造企業(yè)開始認識到數(shù)據(jù)的價值，并開始積極利用數(shù)據(jù)實現(xiàn)業(yè)務(wù)的革新，數(shù)據(jù)已經(jīng)成為推動企業(yè)智能化轉(zhuǎn)型的重要力量。
More and more manufacturing enterprises are beginning to realize the value of data and begin to actively use data to realize the innovation of business. Data has become an important force to promote the intelligent transformation of enterprises.
筆者認為，在制造企業(yè)轉(zhuǎn)型的過程中，數(shù)據(jù)將會凸顯其核心價值。只有企業(yè)在充分完成數(shù)字化和智能化改造，打通數(shù)據(jù)流通的各個關(guān)鍵點，數(shù)據(jù)的威力才能得到充分發(fā)揮。隨著智能制造戰(zhàn)略的推進，企業(yè)智能化水平的提高，數(shù)據(jù)必將在未來的工業(yè)轉(zhuǎn)型過程中扮演越來越重要的角色。
The author thinks that in the process of manufacturing enterprise transformation, the data will highlight its core value. Only when the enterprise fully completes digitization and intelligentized transformation, can the data flow through the key points, the power of the data can be fully played. With the advancement of intelligent manufacturing strategy and the improvement of enterprise intelligence level, the data will play an increasingly important role in the future industrial transformation.
