生產(chǎn)與運(yùn)作分析

前言

本教材系列的出版正值中國(guó)學(xué)術(shù)界工業(yè)工程學(xué)科經(jīng)歷巨大發(fā)展、實(shí)際工作中對(duì)工業(yè)工程的概念、方法和工具的使用興趣日漸濃厚之時(shí)。在實(shí)際工作中有效地應(yīng)用工業(yè)工程的手段將無(wú)疑會(huì)提高生產(chǎn)率、工作質(zhì)量、合作的滿意度和效果。該系列中的書(shū)籍對(duì)工業(yè)工程的本科生、研究生和工業(yè)界中需要解決工程系統(tǒng)設(shè)計(jì)、運(yùn)作和管理諸方面問(wèn)題的人士最為適用。

內(nèi)容概要

《Production and Operations Analysis,4th Ed.生產(chǎn)與運(yùn)作分析(第4版)(影印版)》講述了：國(guó)際著名學(xué)者Steven Nahmias所著《生產(chǎn)與運(yùn)作分析》一書(shū)，以其翔實(shí)、精深的內(nèi)容和嚴(yán)謹(jǐn)?shù)捏w系著稱，被很多國(guó)際著名的大學(xué)工業(yè)工程科系選為教材。該書(shū)內(nèi)容涵蓋了生產(chǎn)與運(yùn)作系統(tǒng)和過(guò)程的各個(gè)方面，包括戰(zhàn)略與競(jìng)爭(zhēng)、預(yù)測(cè)、綜合計(jì)劃、對(duì)已知需求與不確定需求的庫(kù)存控制、供應(yīng)鏈管理、推動(dòng)式與牽引式生產(chǎn)控制系統(tǒng)、作業(yè)調(diào)度、項(xiàng)目管理、質(zhì)量保證、可靠性與維護(hù)等。書(shū)中論述條理清晰，易于被學(xué)生接受；擁有大量實(shí)際案例，特別是提供了一系列精彩的精簡(jiǎn)應(yīng)用(Snapshot Application)實(shí)例，為學(xué)生提供學(xué)以致用的模板。書(shū)中例題與習(xí)題不僅數(shù)量眾多，而且由淺入深，引導(dǎo)學(xué)生舉一反三，對(duì)鞏固知識(shí)、培養(yǎng)能力頗有裨益。
該書(shū)可以作為工業(yè)工程專業(yè)本科生“生產(chǎn)運(yùn)作管理”或“生產(chǎn)計(jì)劃與控制”課程的教材，亦可作為“生產(chǎn)系統(tǒng)”、 “設(shè)施規(guī)劃”、 “項(xiàng)目管理”、 “質(zhì)量管理”等課程的參考書(shū)。

作者簡(jiǎn)介

作者：(美國(guó))Steven Nahmias

書(shū)籍目錄

Chapter 1 Strategy and Competition3Appendix 1-A Present Worth Calculations51Chapter 2 Forecasting55APPendix 2-A Forecast Errors for Moving Averages and Exponential Smoothing106Appendix 2-B Derivation of the Equations for the Slope and Intercept for Regression Analysis108Appendix 2-C Glossary of Notation for Chapter 2109Chapter 3 Aggregate Planning 113Appendix 3-A Glossary of Notation for Chapter 3157Supplement 1 Linear Programming 161Chapter 4 Inventory Control Subject to Known Demand193Appendix 4-A Mathematical Derivations for Multiproduct Constrained EOQ Systems239Appendix 4-B Glossary of Notation for Chapter 4 240Chapter 5 Inventory Control Subject to Uncertain Demand243Appendix 5-A Notational Conventions and Probability Review 293Appendix 5-B Additional Results and Extensions for the Newsboy Model294Appendix 5-C Derivation of the Optimal(Q，R)Policy 296Appendix 5-D Probability Distributions for Inventory Management297Appendix 5-E Glossary of Notation for Chapter 5300Chapter 6 Supply Chain Management 305Chapter 7 Push and Pull Production Control Systems：MRP and 1IT355Appendix 7-A Optimal Lot Sizing for Time-Varying Demand 406Appendix 7-B Glossary of Notation for Chapter 7 410Chapter 8 Operations Scheduling 413Supplement 2 Queuing Theory 473Chapter9 Project Scheduling503Appendix 9．A Glossary of Notation for Chapter 9554Chapter 10 Facilities Layout and Location 557Appendix 10-A Finding Centroids626Appendix 10-B Computing Contour Lines 628Chapter 11 Quality and Assurance 635Appendix 11-A Approximating Distributions 706Appendix 11-B Glossary of Notation for Chapter ll on Quality and Assurance708Chapter 12 Reliability and Maintainabilitv 713Appendix 12-A Glossary of Notation on Reliability and Maintainabilitv 767Appendix：Tables 771Index 789

章節(jié)摘錄

插圖：One uses the frequency histogram to estimate the probability that the number of copies of the Journal sold in any week is a specific value.These probability estimates are obtained by dividing the number of times that each demand occurrence was observed during the year by 52.For example,the probability that demand iS 10 is estimated to be 2／52=.0385.and the probability that the demand is 15 is 5／52=.0962.The collection of a11 of the probabilities iS known as the empirical probability distribution.Cumulative prObabilities alSO can be estimated in a similar Way.For example，the probability that there are nine or fewer copies of the Journal sold in any week iS（1+0+0+0+3+1+2+2+4+6）=19／52=.3654.Although empirical probabilities can be used in subsequent analysis，they are inconvenient for.a number of reasons.First，they require maintaining a record of the demand history for every item.This can be costly and cumbersome.Second.the distribution must be expressed rin this case）as 23 different probabilities.Other items may have an even wider range of past Values.Finally，it is more difficult to compute optimal inventory policies with empirical distributions.For these reasons，we generally approximate the demand history using a continuous distribution.The form of the distribution chosen depends upon the his- torv of past demand and its ease of use.By far the most popular distribution for inventory applications is the normal.One reason is the frequency with which it seems to accurately model demand fluctuations Another is its convenience.The normal model of demand must be used with care，however，as it admits the possibility of negative Values.When using the norrflal distribution to describe a nonnegative phenomenon such as demand，the likelihood of a negative observation should be Suffciently small（less than.01 should SUffice for most applications） so as not to be afactor.

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《Production and Operations Analysis,4th Ed.生產(chǎn)與運(yùn)作分析(第4版)(影印版)》是由清華大學(xué)出版社出版的。

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