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供应链管理

Supply Chain Management

课程介绍 Course Introduction

学分：3 | 先修课：运筹学、生产运作管理 | 学期：春季

供应链管理研究从原材料采购到最终产品交付给客户的整个物流、信息流和资金流的协调与优化。课程内容包括供应链战略、需求预测、库存管理与控制、采购与供应商管理、运输与配送管理、网络设计、供应链协调、牛鞭效应、风险管理、可持续供应链等。学生将学习运用定量模型和定性分析方法，解决供应链中的实际决策问题。

Supply Chain Management studies the coordination and optimization of material flow, information flow, and financial flow from raw material procurement to final product delivery to customers. Topics include supply chain strategy, demand forecasting, inventory management and control, purchasing and supplier management, transportation and distribution management, network design, supply chain coordination, bullwhip effect, risk management, and sustainable supply chains. Students learn to apply quantitative models and qualitative analysis to solve practical supply chain decision problems.

大作业 Final Project

作业标题：供应链优化方案

优化供应链流程，设计库存策略和运输方案，撰写优化报告。

Optimize supply chain processes, design inventory strategies and transportation plans, and write optimization reports.

实施步骤 Implementation Steps

📋 示例：优化一个真实的供应链网络，比如一家电商企业的华东区配送体系。你需要选择3个候选仓库地址、确定安全库存水平和运输路线，然后用Excel Solver或Python建立优化模型，算算总物流成本能不能降低15%。
步骤 1
现状分析
本步骤对工业工程问题进行系统分析，识别问题本质和改进机会。工业工程以系统优化为核心，通过数据分析和流程建模，从效率、质量、成本多个维度评估系统现状。采用价值流图、流程分析、数据统计等方法诊断问题根源。

• 进行现场调研和数据收集，使用秒表法、工作抽样法或视频分析法获取作业时间数据
• 绘制价值流图(VSM)或流程图，识别瓶颈工序、浪费环节和改进点
• 运用统计学方法进行数据分析，区分偶然波动和异常因素，确定关键影响变量
产出：现状分析报告（含数据收集表、流程图/价值流图、问题诊断、改进机会分析） ｜ 质量标准：数据充分、分析深入、问题定位准确、改进机会清晰
步骤 2
方案制定
本步骤是工业工程项目的重要环节，运用IE理论和方法系统优化生产与服务系统。工业工程以提高效率、降低成本、保证质量为目标，强调系统观念和持续改进。采用定量化分析方法和专业工具确保改进效果。

• 运用工业工程基础方法（方法研究、作业测定、流程分析）诊断和改进系统
• 使用专业工具（Arena/Flexsim/Minitab/Lingo等）进行建模、仿真和数据分析
• 从技术、经济、人因多角度评价方案，确保系统整体最优
产出：工业工程报告（含现状分析、改进方案、效果预测、实施建议） ｜ 质量标准：方法科学、数据充分、方案可行、效果显著
步骤 3
计划实施
本步骤是工业工程项目的重要环节，运用IE理论和方法系统优化生产与服务系统。工业工程以提高效率、降低成本、保证质量为目标，强调系统观念和持续改进。采用定量化分析方法和专业工具确保改进效果。

• 运用工业工程基础方法（方法研究、作业测定、流程分析）诊断和改进系统
• 使用专业工具（Arena/Flexsim/Minitab/Lingo等）进行建模、仿真和数据分析
• 从技术、经济、人因多角度评价方案，确保系统整体最优
产出：工业工程报告（含现状分析、改进方案、效果预测、实施建议） ｜ 质量标准：方法科学、数据充分、方案可行、效果显著
步骤 4
效果评估
本步骤对工业工程方案进行综合评价，从技术、经济、社会多维度评估方案价值。综合评价是决策的重要依据，通过建立评价指标体系，运用科学的评价方法，客观比较不同方案的优劣。需考虑定量和定性因素，形成全面的评价结论。

• 建立评价指标体系，包括技术指标（效率、质量、可靠性）、经济指标（投资、成本、收益）和社会指标（安全、环保、人机）
• 运用层次分析法(AHP)、模糊综合评价或TOPSIS等方法进行多指标综合评价
• 进行经济评价，计算投资回收期、净现值(NPV)、内部收益率(IRR)等指标
产出：综合评价报告（含指标体系、评价方法、计算过程、结果分析、推荐方案） ｜ 质量标准：指标全面、方法科学、结果客观、决策支持有效
步骤 5
持续改进
本步骤对工业系统进行优化改进，在满足约束条件下寻求系统性能的最优解。工业工程优化涉及多目标决策，需在效率、质量、成本、交付等多个目标间寻求平衡。采用精益生产、六西格玛、运筹学等方法持续改进系统性能。

• 确定优化目标和约束条件，建立优化模型，选择合适的优化算法（遗传算法、粒子群、模拟退火等）
• 运用精益生产工具（5S、SMED、看板、TPM等）消除浪费，提高生产效率和质量
• 进行多方案比较和敏感性分析，评估优化效果和风险，选择技术经济最优方案
产出：优化方案（含优化模型、改进措施、效果预测、成本效益分析、实施路线图） ｜ 质量标准：目标明确、方法得当、效果显著、可实施性强

Steps

Step 1
Situation Analysis
This step performs systematic analysis of industrial engineering problems, identifying the nature of problems and improvement opportunities. Industrial engineering focuses on system optimization, evaluating system status from efficiency, quality, cost dimensions through data analysis and process modeling. Diagnose root causes using value stream mapping, process analysis, statistical data and other methods.

• Conduct site investigation and data collection, obtain operation time data using stopwatch method, work sampling or video analysis
• Draw value stream map (VSM) or process flow chart, identify bottleneck processes, waste links and improvement points
• Apply statistical methods for data analysis, distinguish random fluctuations from abnormal factors, determine key influencing variables
Deliverable: Current state analysis report (including data collection table, process flow/VSM, problem diagnosis, improvement opportunity analysis) | Quality standard: Sufficient data, in-depth analysis, accurate problem定位, clear improvement opportunities
Step 2
Plan Development
This step is an important element in industrial engineering projects, using IE theory and methods to systematically optimize production and service systems. Industrial engineering aims to improve efficiency, reduce costs and ensure quality, emphasizing system concept and continuous improvement. Adopt quantitative analysis methods and professional tools to ensure improvement effects.

• Apply industrial engineering basic methods (method study, work measurement, process analysis) to diagnose and improve systems
• Use professional tools (Arena/Flexsim/Minitab/Lingo, etc.) for modeling, simulation and data analysis
• Evaluate schemes from technical, economic, ergonomic perspectives, ensuring overall system optimization
Deliverable: Industrial engineering report (including current state analysis, improvement scheme, effect prediction, implementation suggestions) | Quality standard: Scientific method, sufficient data, feasible scheme, significant effects
Step 3
Implementation
This step is an important element in industrial engineering projects, using IE theory and methods to systematically optimize production and service systems. Industrial engineering aims to improve efficiency, reduce costs and ensure quality, emphasizing system concept and continuous improvement. Adopt quantitative analysis methods and professional tools to ensure improvement effects.

• Apply industrial engineering basic methods (method study, work measurement, process analysis) to diagnose and improve systems
• Use professional tools (Arena/Flexsim/Minitab/Lingo, etc.) for modeling, simulation and data analysis
• Evaluate schemes from technical, economic, ergonomic perspectives, ensuring overall system optimization
Deliverable: Industrial engineering report (including current state analysis, improvement scheme, effect prediction, implementation suggestions) | Quality standard: Scientific method, sufficient data, feasible scheme, significant effects
Step 4
Evaluation
This step performs comprehensive evaluation of industrial engineering schemes, assessing scheme value from technical, economic and social dimensions. Comprehensive evaluation is an important basis for decision-making, objectively comparing pros and cons of different schemes through establishing evaluation indicator system and applying scientific evaluation methods. Must consider quantitative and qualitative factors to form comprehensive evaluation conclusions.

• Establish evaluation indicator system, including technical indicators (efficiency, quality, reliability), economic indicators (investment, cost, revenue) and social indicators (safety, environmental protection, ergonomics)
• Apply methods such as AHP, fuzzy comprehensive evaluation or TOPSIS for multi-indicator comprehensive evaluation
• Conduct economic evaluation, calculate payback period, NPV, IRR and other indicators
Deliverable: Comprehensive evaluation report (including indicator system, evaluation method, calculation process, result analysis, recommended scheme) | Quality standard: Comprehensive indicators, scientific method, objective results, effective decision support
Step 5
Continuous Improvement
This step performs optimization and improvement of industrial systems, seeking optimal solutions for system performance under constraint conditions. Industrial engineering optimization involves multi-objective decision-making, requiring balance among efficiency, quality, cost, delivery and other objectives. Continuously improve system performance using lean production, six sigma, operations research and other methods.

• Determine optimization objectives and constraints, establish optimization model, select appropriate optimization algorithms (genetic algorithm, particle swarm, simulated annealing, etc.)
• Apply lean production tools (5S, SMED, Kanban, TPM, etc.) to eliminate waste, improve production efficiency and quality
• Conduct multi-scheme comparison and sensitivity analysis, evaluate optimization effects and risks, select the optimal techno-economic scheme
Deliverable: Optimization scheme (including optimization model, improvement measures, effect prediction, cost-benefit analysis, implementation roadmap) | Quality standard: Clear objectives, appropriate methods, significant effects, strong implementability
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