作业成本法的经济生产批量模型

应用作业成本法(ABC)于传统的经济生产批量问题.这一模型不仅考虑了库存补货成本、库存持有成本和缺货成本,同时还考虑了生产批量和生产周期成本.通过Lingo进行数值计算,结果显示新模型优于传统的模型.     

库存依赖性需求条件下具有库容约束的订货批量模型

构建了瞬时库存依赖性需求条件下具有库容约束的单一零售商品订货批量模型,提出了模型的求解方法和算法步骤,给出算例并进行了灵敏度分析.利用该模型不仅可以求解在给定库容条件下,零售商品的最优订货周期和最优订货批量,而且还可以利用灵敏度分析的结果对库容进行决策.     

成组生产管理研究

对成组生产管理问题进行研究既是新技术革命的要求,也是成组技术发展的要求。成组生产管理主要从生产计划工作和生产作业计划工作中体现出成组技术的特点。成组产品是生产计划的基本对象,可用线性规划组来实现生产计划的优化。成组作业针划分批量问题和排序问题。在产品零件需求量较大且较稳定时,可用经济批量法制定出标准生产间隔期和成组批量;而在产品零件需求量小且不稳定时,需用MRP方法确定浮动批量,以实现成组生产的优化。分枝定界法是成组排序的有效方法,本文较详细地介绍了其用法。     

多产品生产计划与设备维修整合优化模型

将有限长度的生产计划期,合理地分成若干个等时间长度的时段。基于给定的各时段每种产品的需求量以及延迟时间理论,建立数学规划模型,同时优化设备维修和生产计划问题,即确定生产计划期内对设备进行预防性维修的最优时间间隔以及各种产品在每一个时段的最优生产批量大小,使得生产计划期内的产品生产费用、库存费用、延迟交货费用、设备调整费用以及设备维修费用的总和达到最小。并运用数值案例对所建立的模型进行了计算分析。     

浅谈作业成本法相对于传统成本法的先进性

作业成本法是以作业(activity)为核心,确认和计量耗用企业资源的所有作业,将耗用的资源成本准确地计入作业,然后选择成本动因,将所有作业成本分配给成本计算对象(产品或服务)的一种成本计算方法。与传统成本法相比,作业成本法在提高成本信息的真实性,以及基于成本信息的管理和决策的科学性方面,都体现本质上的先进性。     

面向生产调度评估的ABC成本计算模型

为了有效评估调度方案的经济性,提出了一种改进的作业成本计算模型.从ERP的角度对制造资源进行了分类,建立了基于价值链的作业模型,提出了三阶段作业成本计算模型,并对模型的求解过程进行了详细阐述.通过一个案例,分别采用传统成本法和新提出方法计算产品生产成本,并对结果进行了对比分析,证明提出的新方法可以有效地评估调度质量.     

模糊环境下再制造系统批量调度研究

针对再制造系统多种不确定因素,包括回收质量、准备时间、加工时间等,研究面向再制造系统的批量调度问题.考虑回收产品存在质量差异的情况,将回收品划分为几种质量不同的工件组类型,各工件组内所有工件的准备时间和加工时间相同,为了减小准备时间和子系统切换时间,将同一工件组内的工件分批量进行调度处理.在满足交货期、加工次序和机器有限等约束条件下,以加权完工时问最小化为目标,建立了模糊环境下的混合整数规划调度模型.该问题包含了工件分批次和调度顺序两个子问题,使用遗传算法进行求解,结合实际算例得出调度策略,验证了该模型在处理再制造生产调度问题上的有效性,并进一步分析了不同批量大小对再制造调度结果的影响.     

一种面向可重构ERP系统的作业成本法

在对传统企业资源计划(ERP)中的成本方法和传统作业成本法的缺点进行分析的基础上,提出了一种面向可重构ERP系统的作业成本法.该方法建立在广义工作中心的动态可扩展结构基础之上,由将企业资源消耗分配到基本工作中心、将基本工作中心资源消耗分配到作业、将作业资源消耗分配到成本对象以及各级广义工作中心成本滚加计算等四个步骤组成.该方法继承了传统作业成本法面向过程的特点,能够支持过程重构驱动的ERP系统企业内和企业间重构,实现了最大程度降低过程结构成本.算例表明,与传统制造成本法和作业成本法相比,该方法能够为可重构ERP系统提供更有效、准确和集成化的成本信息和决策支持.     

圆钢热轧批量调度的多目标优化方法

针对圆钢热轧批量调度问题,考虑热轧工艺约束、综合生产需求优化等因素,建立了以最小化最大完工时间、机器调整成本以及提前\拖期时间为目标的优化模型,并构造了基于种群修复的改进强度Pareto进化算法。算法以改进强度Pareto进化算法为框架实现批量序列调整,并结合问题变量的离散性特征设计编码规则,以及选择、交叉和变异等遗传进化方式;考虑问题约束的特殊性,设计种群修复策略,以修正违反热轧工艺约束的批量序列。通过基于实际生产数据的仿真实验验证了模型和算法的可行性和有效性。     

采购与多层生产计划问题的协同优化

针对生产与采购这两项企业的重要活动,建立了一种采购计划和多层生产计划的集成优化模型,将采购计划、批量计划以及作业排序这三层计划问题进行综合决策。为求解该问题,设计了一种遗传算法和网络优化方法相结合的协同优化策略,遗传算法中每一个个体同时包含了批量计划和作业排序,并调用网络优化模型得出订购策略。数值仿真实验显示了提出的方法求解该类集成优化问题的良好性能。通过与独立优化方法进行比较,显示了协同优化策略的优越性。     

Economic production quantity models for deteriorating items with rework and stochastic preventive maintenance time

Economic production quantity (EPQ) models for deteriorating inventory have been investigated by many researchers in recent years. In this paper, we develop EPQ models for deteriorating items with rework and stochastic preventive maintenance time. The models are solved using a search method, since a closed form solution cannot be derived. A numerical example and sensitivity analysis are provided to evaluate the models. The sensitivity analysis shows that the deteriorating cost has a significant effect on the optimal inventory cost; however, the production and the demand rate have the most significant effect on the optimal total cost and the optimal production up-time period.     

Joint production and shipment lot sizing for a delivery price-based production facility

A joint economic production quantity (EPQ) and delivery quantity model for a production system is investigated in this paper. More specifically, an EPQ policy is implemented in the production system, while a smaller shipping quantity is periodically dispatched to the customer. The production system is also responsible for the shipment cost, i.e. a delivery price-based procurement from the customer. The considered cost includes setup cost to launch the batch production, inventory carrying cost, and transportation cost, where the transportation cost is a function of the delivery quantity. A per unit time cost model is developed and analysed to determine the optimal production and delivery quantities. Under some mild conditions, it can be shown that the joint cost function is convex with respect to the production quantity; and the number of delivery is an integer in each replenishment cycle. Computational study has demonstrated the significant impact of the joint decision model on the operating cost. In particular, the reduction in total cost can be more than 15% when inventory carrying costs, and/or transportation costs, are high.     

Determining the optimal lot size for the finite production model with random defective rate,the rework process,and backlogging

This paper considers the effects of the reworking of defective items on the economic production quantity (EPQ) model with backlogging allowed. The classic EPQ model assumes that manufacturing facility functions perfectly during a production run. However, due to process deterioration or other factors, the production process may shift and produce imperfect quality items. In this study, a random defective rate is considered, and when regular production ends, the reworking of defective items starts immediately. Not all of the defective items are reworked, a portion of them are scrap and are discarded. Repairing and holding cost per reworked item and disposal cost per scrap item are included in the proposed mathematical modelling and analysis. The renewal reward theorem is utilized to deal with the variable cycle length, and the optimal lot size that minimizes the overall costs for the imperfect quality EPQ model is derived where backorders are permitted.     

An integrated EPQ model based on a control chart for an imperfect production process

The notion of quality control is introduced into the classic economic production quantity (EPQ) model. Based on previous research, this paper contributes to an integrated EPQ model combining the concepts of statistical process control and maintenance. An imperfect production process involving three different conditions is considered. A control chart is adopted to monitor the whole process with Taguchi's loss function estimating the quality cost of each condition. A corresponding maintenance policy is planned for the machine depending on what condition it runs in. Thus the proposed EPQ model takes quality-related costs and maintenance-related costs into account other than storage costs and ordering costs already considered in the classic model. The objective of this model is to minimise the total expected production cost per production cycle while simultaneously determining the optimal parameters of control chart design, the interval between sampling, the sample size and the maintenance decision policy. The pattern search method is used to solve the problem using the MATLAB toolbox. In addition, a case study, sensitivity analysis and comparison analysis are presented to demonstrate the application of the model.     

Economic production quantity model for deteriorating inventory with random machine unavailability and shortage

Both random machine unavailability and shortage are common occurrences in manufacturing industries. In this paper, machine unavailability is considered in deriving an economic production quantity (EPQ) model for deteriorating items. We develop four EPQ models for deteriorating inventory with random machine unavailability and shortage. The study considers lost sales, backorder and two kinds of machine unavailability distributions. Numerical examples are provided to illustrate the theory. Key parameter changes that affect costs are shown in the sensitivity analysis. From the results of the sensitivity analysis, it is shown that the random machine unavailability parameter and holding cost have significant effects on the optimal total cost and production down-time.     

A production quantity model for imperfect quality items with shortage and screening constraint

This study develops an economic production quantity (EPQ) model and solution procedure for imperfect items with shortage and screening constraint. The Renewal Reward Theorem (RRT) is applied to formulate the exact expected total profit per unit time. We have shown the robustness of our model using time interval as decision variable rather than the traditional order size and backorder quantity. A solution procedure is provided to derive the optimal policy. Special cases of the EOQ/EPQ models can be obtained by taking the parameter limiting values. Numerical examples and sensitivity analysis are presented to verify our results.     

经济生产批量与CUSUM控制图最优化联合设计

针对传统经济生产批量一般以完美生产过程为对象,质量成本通常也仅以符合规格为判断的标准等问题,提出了一种考虑田口损失函数的将经济生产批量与累积和控制图联合设计的模型。对于生产过程,提出了一种更符合实际情况的三阶段的制造过程,建立了考虑均值随机偏移的三阶段损失模型,并以此为基础,建立了综合考虑包括质量损失及与批量相关的储存成本、订货成本等在内的总期望成本,目的是获得最优化的经济生产批量和累积以及控制图参数设计联合模型,并使生产过程的总期望成本最小。采用行径搜索法对模型进行求解,并举出数值例子进行比较和参数敏感度分析加以说明模型的应用情况。     

Integrating the economic production model with deteriorating raw material over multi-production cycles

This paper considers an Economic Production Quantity (EPQ) model with deteriorating raw material and investigates the impact of deterioration on the production process. The EPQ base case with no deterioration is presented where raw material is ordered for multiple production cycles. We present the differential equations to calculate the on-hand inventory of raw material and present closed-forms expressions for the required order of raw material to result in a desired amount of effective raw material per order cycle. Closed-form expression for the total profit per unit time is obtained and we solve for the optimal production quantity of finished product per production cycle and the order quantity of raw material. We present numerical examples where we compare our model to a system which ignores the impact of deterioration and results in shorter production cycles due to an insufficient amount of effective raw material.     

Economic production quantity (EPQ) model with partial backordering and a discount for imperfect quality batches

Economic production quantity (EPQ) models are traditionally used in operations management. Despite the large number of papers that describe the models, the classic EPQ model does not consider either imperfect quality batches or shortages. However, some industries may be able to sell imperfect items for a lower price, reducing the total production cost. This paper proposes an EPQ model with partial backordering and discount for imperfect quality batches and an algorithm that returns optimal values for the problem. From a numerical example, it is possible to analyse how the changes in the variables affect each part of the total cost function, which provides a useful tool for strategic decision-making. We conclude that it is better to sell imperfect items as soon as possible because the savings in holding costs results in a total cost reduction. It is more profitable for the producer to have planned shortages considering that some costumers are willing to wait. Furthermore, the reduction of the goodwill cost does not necessarily reduce the total cost.     

An integrated material flow system approach for determining the economic production quantity (EPQ)

Traditionally, the analysis of material flow systems has focused on each of the individual components of the system separately (i.e. material handling, production lot size, unit load size, flow path, layout, space, etc). Even though each component is difficult to address on its own, it is imperative that they be addressed concurrently due to their interactions. This paper explores the relationships between the components in the material flow system with respect to determining the economic production quantity (EPQ). This is in contrast to the traditional EPQ model, which considers only set-up cost, inventory cost, and demand, while ignoring other material flow system issues. A multi-item economic production quantity model under a storage space limit is considered with respect to material handling equipment selection and requirements, unit load size, and flow path selection. The integrated material flow system problem is mathematically formulated as a large scale, nonlinear integer programming model, and a heuristic solution procedure is developed. The impact of using an integrated approach to determine the EPQ is illustrated and solutions are compared to both a lower bound and a traditional sequential approach. It is found that an integrated approach provides consistent and significant improvement in the overall solution quality.