本文選題：傳送帶給料加工站 + 產(chǎn)銷一體化模式��； 參考：《合肥工業(yè)大學(xué)》2014年碩士論文

【摘要】：現(xiàn)實(shí)世界的一些生產(chǎn)制造業(yè)中,通常存在一類配有恒速傳送帶的生產(chǎn)中心,工件隨機(jī)到達(dá)生產(chǎn)中心進(jìn)行必要的加工。通常,為了提高生產(chǎn)線的柔性生產(chǎn),加工站配置一個(gè)有限容量的緩沖庫(kù)用于臨時(shí)存儲(chǔ)工件,這類源于福特生產(chǎn)線的生產(chǎn)模型叫做傳送帶給料加工站(Conveyor-Serviced Production Station,簡(jiǎn)稱CSPS). CSPS可以被視為生產(chǎn)自動(dòng)化過(guò)程中的抽象模型,例如機(jī)器人生產(chǎn)線。作為一類智能生產(chǎn)模型,CSPS被廣泛用在現(xiàn)實(shí)生產(chǎn)中。因此研究該類系統(tǒng)的最優(yōu)控制問題,具有重要的現(xiàn)實(shí)意義,也是工業(yè)工程中的一個(gè)重要領(lǐng)域。 現(xiàn)今,由于在供應(yīng)鏈管理(SCM)時(shí)代經(jīng)濟(jì)發(fā)展的影響,實(shí)時(shí)的生產(chǎn)可能會(huì)極大地受到影響了市場(chǎng),因此本文主要研究產(chǎn)銷一體化模式下傳送帶給料加工站系統(tǒng)的優(yōu)化控制,該類系統(tǒng)被視為一個(gè)連接到銷售中心的生產(chǎn)中心,加工后的成品流入銷售中心的成品庫(kù),本系統(tǒng)的特點(diǎn)是隨機(jī)的工件到達(dá)和顧客到達(dá),隨機(jī)的加工時(shí)間和有限的緩沖庫(kù)和成品庫(kù)容量。所以類似這類產(chǎn)銷一體化模式下CSPS系統(tǒng)的控制策略受生產(chǎn)和銷售水平的共同影響。本文主要目標(biāo)是隨機(jī)控制問題的建模和提供解決方法以得到平均和折扣準(zhǔn)則下的最優(yōu)前視控制策略。這部分首先為產(chǎn)銷一體化模式下CSPS系統(tǒng)建立詳細(xì)的以緩沖庫(kù)和成品庫(kù)剩余量為聯(lián)合狀態(tài)的半Markov決策過(guò)程,在系統(tǒng)參數(shù)精確已知的情況下可以通過(guò)數(shù)值迭代和策略迭代求解該問題。為了避免理論優(yōu)化算法中“維數(shù)災(zāi)”和“建模難”的問題,文中給出基于模擬退火的Q-學(xué)習(xí)算法以推導(dǎo)近似解。最后仿真結(jié)果表明,通過(guò)我們建立的模型和給出的優(yōu)化算法,在緩沖庫(kù)和成品庫(kù)容量設(shè)計(jì)合理的情況下,系統(tǒng)可以得到最優(yōu)或者次優(yōu)前視控制策略。 現(xiàn)實(shí)生產(chǎn)中,生產(chǎn)加工站的服務(wù)率是決定系統(tǒng)運(yùn)行效率的關(guān)鍵之一,因此對(duì)服務(wù)率進(jìn)行合適地控制可以提高系統(tǒng)的生產(chǎn)率,減少等待時(shí)間和周期時(shí)間,從而使系統(tǒng)在一定條件下達(dá)到最優(yōu)。因此本文研究服務(wù)率可變的產(chǎn)銷一體化模式下CSPS系統(tǒng)的優(yōu)化控制,主要目標(biāo)是對(duì)隨機(jī)優(yōu)化控制問題進(jìn)行建模和提供解決方案。首先,以緩沖庫(kù)和成品庫(kù)剩余容量為聯(lián)合狀態(tài),以站點(diǎn)前視距離和工件服務(wù)率為行動(dòng)變量,將該優(yōu)化控制問題建模為半Markov決策過(guò)程。因此,可用策略迭代和基于模擬退火思想的Q-學(xué)習(xí)算法等方法進(jìn)行求解,獲得系統(tǒng)在平均準(zhǔn)則或折扣準(zhǔn)則下的最優(yōu)前視距離和服務(wù)率。
[Abstract]:In some manufacturing industries in the real world, there is usually a kind of production center with constant speed conveyor belt. In order to improve the flexible production of the production line, the processing station is equipped with a limited capacity buffer library for temporary storage of the workpiece. This kind of production model derived from the Ford production line is called the Conveyor-Serviced production Station (CSPS). CSPS can be regarded as an abstract model in the process of production automation, such as a robot production line. As a kind of intelligent production model, CSPS is widely used in practical production. Therefore, it is of great practical significance to study the optimal control problem of this kind of systems, and it is also an important field in industrial engineering. Nowadays, because of the influence of the economic development in the era of supply chain management (SCM), the real-time production may be greatly affected by the market. Therefore, this paper mainly studies the optimization control of the belt feed processing station system under the integrated mode of production and marketing. This kind of system is regarded as a production center connected to the sales center, the finished product after processing flows into the finished product store of the sales center, this system is characterized by the random arrival of the work piece and the arrival of the customer. Random processing time and limited buffer and finished product storage capacity. Therefore, the control strategy of CSPS system is influenced by the production and sales level under the integrated mode of production and marketing. The main goal of this paper is to model the stochastic control problem and provide a solution to obtain the optimal forward view control strategy under the average and discount criteria. In this part, a semi-Markov decision-making process with buffer and finished product surplus as joint state is established for CSPS system under the integrated mode of production and marketing. This problem can be solved by numerical and policy iterations when the system parameters are known accurately. In order to avoid the problems of "dimension disaster" and "difficult modeling" in the theoretical optimization algorithm, a Q- learning algorithm based on simulated annealing is presented to derive the approximate solution. Finally, the simulation results show that the optimal or sub-optimal forward view control strategy can be obtained under the reasonable design of the capacity of the buffer library and the finished product warehouse through the proposed model and the given optimization algorithm. In real production, the service rate of the production and processing station is one of the key factors that determine the efficiency of the system operation. Therefore, proper control of the service rate can improve the productivity of the system and reduce the waiting time and the cycle time. Thus, the system can be optimized under certain conditions. Therefore, this paper studies the optimal control of CSPS system under the integrated mode of production and marketing with variable service rate. The main goal of this paper is to model the stochastic optimal control problem and provide a solution. Firstly, the optimal control problem is modeled as a semi-Markov decision process with the residual capacity of the buffer library and the finished product bank as the joint state, the forward distance of the site and the service rate of the workpiece as the action variables. Therefore, the optimal forward distance and service rate of the system under the average criterion or discount criterion can be obtained by means of strategy iteration and Q-learning algorithm based on simulated annealing.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TB49;TP273

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