【摘要】：隨著經(jīng)濟(jì)社會的轉(zhuǎn)型升級,制造型企業(yè)的競爭加劇,企業(yè)在生產(chǎn)計劃制定、原材料采購和產(chǎn)品銷售等方面需要做到更加精細(xì)化和規(guī)范化,需要對企業(yè)PLM過程中的產(chǎn)品設(shè)計、制造、裝配、入庫、出庫、銷售、退貨及服務(wù)等各環(huán)節(jié)的變化情況進(jìn)行實時監(jiān)測,以過往的企業(yè)生產(chǎn)數(shù)據(jù)為樣本和基礎(chǔ)對企業(yè)未來一段時間內(nèi)的產(chǎn)品生產(chǎn)、銷售等過程進(jìn)行預(yù)測,為企業(yè)制定采購計劃、生產(chǎn)計劃等戰(zhàn)略決策提供數(shù)據(jù)的支撐。本文首先分析了企業(yè)PLM過程中決策支持的重要意義以及數(shù)據(jù)預(yù)測對企業(yè)決策的影響,以企業(yè)過往生產(chǎn)數(shù)據(jù)為研究對象,對如何獲得有效的預(yù)測數(shù)據(jù)以及以友好精美的方式展示給決策者進(jìn)行數(shù)據(jù)預(yù)測的建模和應(yīng)用研究,具體的研究內(nèi)容如下:首先,構(gòu)建了基于ARIMA的數(shù)據(jù)學(xué)習(xí)預(yù)測模型,采用殘差檢驗對模型進(jìn)行校驗,并用方差校驗和T校驗對模型進(jìn)行優(yōu)化處理;接著,采用R語言和基于Java的JSP、Servlet和JavaBean技術(shù)以及rJava相結(jié)合的方法,實現(xiàn)預(yù)警模型求解并進(jìn)行測試驗證與優(yōu)化;然后,構(gòu)建了基于瀏覽器/服務(wù)器結(jié)構(gòu)的決策支持系統(tǒng),在為企業(yè)決策提供支持的同時根據(jù)不斷變動的企業(yè)生成情況對預(yù)測模型進(jìn)行微調(diào);最后,以決策支持系統(tǒng)為基礎(chǔ)建立基于web的應(yīng)用,讓決策者可以及時直觀的了解企業(yè)實時的生產(chǎn)情況。
[Abstract]:With the transformation and upgrading of economy and society, the competition of manufacturing enterprises intensifies. Enterprises need to be more refined and standardized in production planning, raw material procurement and product sales, and need to design products in the process of enterprise PLM. The changes in manufacturing, assembly, warehousing, delivery, sales, return and service are monitored in real time. The production of products in the future will be monitored on the basis and sample of past enterprise production data. Forecast the process of sales and provide data support for strategic decision-making such as purchasing plan and production plan. This paper first analyzes the importance of decision support in PLM process and the influence of data prediction on enterprise decision making. The research on how to obtain effective prediction data and display it to decision makers in a friendly and exquisite way is as follows: firstly, a data learning prediction model based on ARIMA is constructed. The model is calibrated by residual test and optimized by variance check and T check. Then, R language, JSP,Servlet and JavaBean technology based on Java and rJava are adopted to solve the early warning model and test verification and optimization. Then, a decision support system based on browser / server structure is constructed, which can provide support for enterprise decision and fine-tune the prediction model according to the changing situation of enterprise generation. Finally, based on the decision support system (DSS), an application based on web is established, so that the decision-makers can understand the real-time production situation of the enterprise in time and intuitively.
【學(xué)位授予單位】：貴州師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F426.48;TP311.13

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