制造行業(yè)的企業(yè)往往擁有并運(yùn)行大量的工業(yè)設(shè)備，所有這些設(shè)備都需要監(jiān)控和維護(hù)。對(duì)于現(xiàn)有的部署，工業(yè)物聯(lián)網(wǎng)使得基于更精確數(shù)據(jù)的制造過(guò)程中決策的改進(jìn)成為可能。它還可以用來(lái)提高生產(chǎn)質(zhì)量和正常運(yùn)行時(shí)間，因?yàn)閺木W(wǎng)絡(luò)上的設(shè)備和傳感器收集的數(shù)據(jù)可以實(shí)現(xiàn)對(duì)生產(chǎn)設(shè)備的實(shí)時(shí)和預(yù)測(cè)性維護(hù)。
工業(yè)物聯(lián)網(wǎng)背后的主要思想是使機(jī)器在制定決策時(shí)比人類(lèi)更智能、更高效。這依賴(lài)于準(zhǔn)確、一致地捕獲和傳遞數(shù)據(jù)。信立科技多年從事工業(yè)物聯(lián)網(wǎng)的核心產(chǎn)品無(wú)線傳感器，在數(shù)據(jù)的抓取和傳輸上技術(shù)成熟，開(kāi)發(fā)了系列網(wǎng)關(guān)、測(cè)控、傳感裝置，并應(yīng)用到各個(gè)制造業(yè)中，為合作伙伴帶來(lái)了高效率的生產(chǎn)決策基礎(chǔ)。
在大數(shù)據(jù)支撐下，機(jī)器學(xué)習(xí)，系統(tǒng)可以被訓(xùn)練以發(fā)現(xiàn)潛在的模式，這些模式將對(duì)未來(lái)的失敗給出指示。如果結(jié)果是有關(guān)的，他們可以立即調(diào)查。這些信息以前需要花費(fèi)數(shù)周的時(shí)間才能發(fā)現(xiàn)，并依賴(lài)于每個(gè)技術(shù)熟練的專(zhuān)業(yè)人員的可用性。現(xiàn)在，使用實(shí)時(shí)數(shù)據(jù)可以幫助那些擁有合適技能的人在多個(gè)地點(diǎn)監(jiān)控更多的機(jī)器，從而更快地做出維護(hù)決策。反過(guò)來(lái)，制造業(yè)效率可以大大加快。
除了預(yù)測(cè)性維護(hù)以外，機(jī)器學(xué)習(xí)在工業(yè)性能方面也有很大的改進(jìn)。要做到這一點(diǎn)，企業(yè)需要了解所有可用的數(shù)據(jù)，對(duì)數(shù)據(jù)進(jìn)行量化，并根據(jù)收到的信息提供有關(guān)如何最好地進(jìn)行制造過(guò)程的深入見(jiàn)解。機(jī)器學(xué)習(xí)可以用來(lái)演示如何提高性能，并在同一級(jí)別的投資提供更快的結(jié)果。
在制造行業(yè)中，時(shí)間就是金錢(qián)。隨著工業(yè)物聯(lián)網(wǎng)戰(zhàn)略的實(shí)施，從單獨(dú)的傳感器到可用的分析和自動(dòng)化，制造商可以圍繞整體效率和成本做出更好的業(yè)務(wù)決策。工業(yè)物聯(lián)網(wǎng)戰(zhàn)略在可持續(xù)和綠色生產(chǎn)實(shí)踐以及供應(yīng)鏈可追溯性方面也具有很大的潛力。
隨著“循環(huán)經(jīng)濟(jì)”在企業(yè)的應(yīng)用，從產(chǎn)品到包裝的所有要素都應(yīng)該被重復(fù)使用，并在整個(gè)價(jià)值鏈中循環(huán)利用，工業(yè)物聯(lián)網(wǎng)的實(shí)施對(duì)其追蹤結(jié)果至關(guān)重要。
Manufacturing enterprises often own and operate a large number of industrial equipment, all of which need to be monitored and maintained. For existing deployments, the Industrial Internet of Things makes it possible to improve decision-making in manufacturing processes based on more accurate data. It can also be used to improve production quality and uptime, as data collected from devices and sensors on the network enables real-time and predictive maintenance of production equipment.
The main idea behind the industrial Internet of things is to make machines more intelligent and efficient than human beings in making decisions. This depends on accurate and consistent capture and transmission of data. Xinli Technologies has been engaged in wireless sensor which is the core product of industrial Internet of Things for many years. It has developed a series of gateways, measurement and control, sensor devices and applied them to various manufacturing industries. It has brought high-efficiency production decision-making basis for partners.
Supported by large data, machine learning, systems can be trained to discover potential patterns that indicate future failures. If the results are relevant, they can investigate immediately. It took weeks to discover this information and depended on the availability of each skilled professional. Now, using real-time data can help those with the right skills monitor more machines in multiple locations, making maintenance decisions faster. In turn, manufacturing efficiency can be greatly accelerated.
In addition to predictive maintenance, machine learning has also improved in terms of industrial performance. To do this, companies need to understand all the available data, quantify the data, and provide in-depth insights into how best to conduct the manufacturing process based on the information received. Machine learning can be used to demonstrate how to improve performance and provide faster results at the same level of investment.
In manufacturing, time is money. With the implementation of the industrial Internet of Things strategy, from individual sensors to available analysis and automation, manufacturers can make better business decisions around overall efficiency and cost. The industrial Internet of Things strategy also has great potential for sustainable and green production practices and supply chain traceability.
With the application of "circular economy" in enterprises, all elements from products to packaging should be reused and recycled throughout the value chain. The implementation of the Industrial Internet of Things (IOT) is crucial to its tracking results.
