A MIP based heuristic for capacitated MRP systems

Although Material Requirements Planning (MRP) is the most widely used production planning tool in today’s manufacturing companies, its inability to perform an exhaustive capacity planning, lack of a comprehensive and integrated shop floor extension and using constant and inflated lead times necessitate intelligent methods for developing cost effective production plans. A single optimization model might be employed to overcome these limitations, but it would be intractable to use it in large manufacturing systems. Hence, in this paper, we propose a heuristic method called Capacity Allocater and Scheduler, CAS, to eliminate drawbacks of MRP systems and provide solutions for large-scale instances. The CAS procedure, based on iteratively solving relaxed Mixed Integer Programming (MIP) models, is built on a lot sizing and scheduling framework, which considers both supply alternatives and lot size restrictions simultaneously. Finally, we give a detailed numerical example to demonstrate how CAS may be used in practice, and provide our concluding remarks.     

A flexible MRP-DSS with an emphasis on leadtime variations

The conventional MRP systems translate plant requests into production and inventory scheduling actions of the factory. However, the assumption of constant leadtime policy limits MRP's capability in supporting the decision-making processes for better production scheduling control. Obviously, the assumption of constant leadtime is unrealistic in real-world problems.

This paper focuses on the leadtime variations associated with both internal and external manufacturing logistics. Two modeling techniques are used to study the variation of leadtime. First, a stochastic model using simulation and statistical concepts is developed in the analysis of shipment leadtime. Second, a variable leadtime matrix model is used to determine production leadtime. As a result, a flexible material requirements planning decision support system (FMRP-DSS) is developed to determine more accurate leadtimes, and to protect against the uncertainty of the conventional MRP systems. Moreover, the system can be viewed as a transition from the conventional MRP systems to the “Just-In-Time Manufacturing” (JITM) systems.

A “whatif” scenario is designed to integrate the capacities of the FMRP-DSS as a whole to support the decision-making process and to provide a better production and inventory planning environment. FMRP-DSS, which is designed to be highly user-friendly, menu-driven, and interactive, will help the decision-makers in their decision making process of production and inventory planning more effectively and efficiently.     

A new framework for MRP systems to be effective in engineered-to-order environments

Present day manufacturing resource planning (MRP) systems do not perform well in engineered-to-order (ETO) environments. A study of the use of MRP systems by ETO companies has led to the development of a new framework for manufacturing planning systems. New features allow better coordination of activities in the areas of engineering, material acquisition, production, and delivery. The new framework especially addresses the problem of planning with uncertain information which is characteristic of an ETO environment.     

Material requirement planning systems development

Material requirement planning systems are becoming an integral part of many manufacturing information systems. MRP is both a scheduling and control technique designed to minimize inventory investment, to maximize production efficiency, and to improve customer service. The purposes of this paper are to describe the inputs to an MRP system; discuss the logic of an MRP system; and provide examples of various exception reports generated by an MRP system. A listing of an MRP program with documentation is provided, also.     

Advanced Resource Planning

Advanced Resources Planning hits the bottom of what we know as aggregate planning. This approach differs from other approaches in that it explicitly recognizes the stochastic nature of manufacturing systems. Therefore, it is an ideal high-level tuning and planning tool which can be used in various planning environments like MRP, ERP, JIT, Load-Oriented Planning, Theory of Constraints, Finite Scheduling, POLCA systems, and perhaps many more. The main purpose is to set aggregate planning parameters right before diving into any other operational planning decision. In this sense, we opt to offer realistic lead time estimations, lot sizes, utilization levels, customer service levels and quoted delivery times.The underlying approach is a waiting line network, which is heavily adapted in order to make it useful for planning purposes. The main feature is that both input parameters and output parameters are considered as stochastic variables. In this way it allows us to model manufacturing environments in a more realistic and intuitive way, including all kinds of uncertainty and variability. As a consequence, the output of the planning effort is also a stochastic variable: it has an average, a variance and the entire lead time distribution. The latter makes it possible to obtain high customer service levels or to establish realistic delivery times, which can be met with a high probability.This mathematical approach as such is not suited for people operating a manufacturing system. We illustrate the approach with software, named i-CLIPS, and we review some implementations and their results.     

Optimum loading for GT/MRP manufacturing systems

A hierarchical planning procedure to utilize the potential advantages of coexistence of Group Technology (GT) and Material Requirement Planning (MRP) systems is presented. In addition, a multi-period linear programming model is proposed to determine the minimum cost loading schedule of manufacturing cells used in batch production environment. The proposed model provides the optimum work force for each cell over the planning horizon.     

Integrating manufacturing resources planning (MRP II) with flexible manufacturing systems (FMS)

This paper will describe the gap that exists between the Manufacturing Resources Planning (MRP II) system and the Flexible Manufacturing System (FMS) and discuss several approaches for closing the gap. Considerable effort has gone into developing and integrating the various modules in the MRP II system. The modules for business planning, production planning, master production scheduling, material requirement planning, capacity requirements planning, and shop floor control have been integrated into a comprehensive computer package for planning and controlling manufacturing. At the same time, a similar effort has been underway to develop and integrate the several subsystems of a FMS. In particular, a number of computer control systems have been developed to automatically plan and control the operations of NC machines with automated tool changers, automated material handling, and automated test and inspection equipment. Unfortunately these two efforts have proceeded relatively independently with little interaction between the two groups. If computer integrated manufacturing (CIM) is to become a reality, the resulting gap must be closed, and closed rapidly.     

Grid enabled MRP process improvement under distributed database environment

The material requirement planning (MRP) process is crucial when software packages, like enterprise resource planning (ERP) software, are used in the production planning for manufacturing enterprises to ensure that appropriate quantities of raw materials and subassemblies are provided at the right time. Whereas little attention has been paid to the architectural aspects of MRP process in academic studies, in practice, reports are often made of its time consuming characteristics due to intensive interactions with databases and difficulty in real time processing. This paper proposes a grid enabled MRP process in a distributed database environment and demonstrates the performance improvement of the proposed process by a simulation study.     

基于多层C/S结构的饲料行业MRP系统

为适应饲料行业生产管理自动化的需要,设计并实现了基于多层C/S结构即客户机/应用服务器/数据库服务器体系结构的饲料生产行业制造资源计划(MRP)系统,对饲料生产MRP进行了系统分析,介绍了系统的设计方案与体系结构,重点介绍了生产管理模块的设计与实现,对生产管理的主要模块如物料清单(BOM)管理和MRP计算等进行了详细分析.     

CSFs and sources of assistance and expertise in strategic IS planning: a Singapore perspective

Strategic information systems (IS) planning is not an easy task and knowing which critical areas to manage certainly enhances IS planning success. Studies of critical success factors (CSFs) usually dealt with specific systems or management technique implementation, such as manufacturing resource planning (MRP) and total quality management (TQM). There exists little empirical research on CSFs per se in strategic IS planning. This paper is an effort to enhance existing knowledge on how strategic IS planning should be effectively managed. Using data from a survey on IS planning conducted in 1996 by the National University of Singapore, we identified and rank-ordered the CSFs in strategic IS planning in the Singapore context. We also examined the sources of assistance and expertise that companies undertaking IS planning in Singapore can tap.     

Design and manufacturing of sheet-metal parts: Using features to aid process planning and resolve manufacturability problems

This paper describes an integrated system for the design and production of sheet-metal parts. We have identified some important features for the sheet-metal bending process. These features are automatically generated as the design progresses. After the designs are complete, our automatic process planning system uses the features and generates new ones to aid the production of plans with near-minimum manufacturing costs. Finally, these plans are used to produce parts on an automatic bending system.Once a plan is generated, it can be used to manufacture the part, and to provide feedback to design and other factory systems. The application of features and the potential feature interaction problems are discussed. Several key manufacturing problems are also considered and the result of planning is used to resolve these problems. By solving these feature interaction problems and often practical manufacturing issues, we are able to plan and manufacture the majority of the parts we have tested less than one hour after the flat patterns are prepared.     

CIM implementation through at and MRP integration

A CIM implementation case is introduced in this paper. It is accomplished through the integration of two fundamental approaches to production plammng and control; Jrr and MRP. The resultant system is a hybrid where some JIT methodologies prevail, but the benefits of the MRP are also required A new BOM structure is designed for the load leveled production with small lot size and the synchronized production. The overall production planning concept is described with actual data.     

Temporal reasoning for manufacturing: A hybrid representation and complexity management

Temporal considerations play a key role in the planning and operation of a manufacturing system. The development of a temporal reasoning mechanism would facilitate effective and efficient computer-aided process planning and dynamic scheduling. We feel that a temporal system that makes use of the expressive power of the integral language and the computational ease of the point language will be best suited to reasoning about time within the manufacturing system. The concept of a superinterval, or a collection of intervals, is used to augment a hybrid point-interval temporal system. We have implemented a reasoning algorithm that can be used to aid temporal decision making within the manufacturing environment. Using the quantitative results obtained by measuring our program's performance, we show how the superinterval can be used to partition large temporal systems into smaller ones to facilitate distributed processing of the smaller systems. The distributed processing of large temporal systems helps achieve real-time temporal decision-making capabilities. Such a reasoning system will facilitate automation of the planning and scheduling functions within the manufacturing environment and provide the framework for an autonomous production facility.     

Lot-sizing decisions for material requirements planning with hybrid uncertainties in a smart factory

Material requirements planning (MRP) is a kind of medium-term production planning, which aims to plan the end item requirements of the master production schedule over a finite planning horizon. In a smart factory, the customer requirements and the production status are varying in time, which increases the uncertainties in making lot-sizing decisions for MRP. In this study, a hybrid chance-constrained programming (HCCP) model is developed for solving an MRP problem with hybrid uncertainties, in which both randomness and fuzziness exist in a lot-sizing decision process. The objective of the HCCP model is to determine the lot sizes of all items while satisfying the stochastic demands and the fuzzy capacity constraints. The credibility and probability are incorporated into the proposed model to measure the fuzziness and randomness, respectively. In order to solve the model, relevant approaches for converting the probability-based and credibility-based constraints into the equivalent deterministic forms are proposed. Decision makers can set different confidence levels according to their own risk preferences to get different results. Finally, an example is presented to verify that the approach proposed in this paper is feasible for solving MRP problems with hybrid uncertainties.     

基于MRP汽车零部件生产计划系统研究与实现

为了提高汽车零部件生产效率，确保按时完成客户订单，将物料需求计划（MRP）技术应用于汽车零部件生产计划系统中．首先给出了汽车零部件行业的供应链结构，提出了基于MRP的对产品进行分组并对产品结构进行层次化分解的汽车零部件生产计划模式．在此基础上，详细介绍了利用客户订单、产品结构信息、工作日历以及库存信息等来生成零部件生产计划和所需物料的采购计划的实现过程，并对实例进行了分析．该系统已经应用于汽车零部件生产企业中．     

重型机械生产MRP算法改进及其应用

针对重型机械生产模式,提出了一种“计划压缩”MRP改进算法,该算法继承了MRP的基本思想,根据物料清单将主生产计划分解成零部件的生产计划和原材料、采购件的采购计划,并在此基础上对MRP算法进行改进,根据交货期,利用压缩提前期倒排计划,将生产计划排到工序级。经实例证明采用这种MRP算法,增加了排产的灵活性,提高了排产效率,有效地减少了订单拖延的情况。     

Evaluating the interaction between the manufacturing environment and planning and control systems

The choice of an appropriate infrastructure (systems and organizations) that is used to support the manufacturing process is often treated lightly in the literature. Historically, the selection of manufacturing planning and control systems has been influenced more by current “new wave” rather than by the environment faced by the firm. This study explores the interaction between the manufacturing environment and the planning and control system as it relates to performance. A mail survey of sample companies is used to classify manufacturing firms along the dimensions of production process, production volumes and the type of planning and control system used, and to estimate the processes-environment fit. Manufacturing performance is assessed through measures of inventory turnover, customer service, and delivery lead time. A random coefficient regression model is used to investigate if the fit between the manufacturing environment and planning and control systems is related to manufacturing performance.     

Hierarchical production planning with demand constraints

This paper explores the hierarchical production planning (HPP) problem of flexible automated workshops (FAWs), each of which has a number of flexible manufacturing systems (FMSs). The objective is to decompose medium-term production plans (assigned to an FAW by ERP/MRP II) into short-term production plans (to be executed by FMSs in the FAW) so as to minimize cost on the condition that demands have just been met. Herein, the HPP problem is formulated by a linear programming model with the overload penalty different from the underload penalty and with demand constraints. Since the scale of the model for a general workshop is too large to be solved in the simplex method on a personal computer within acceptable time, Karmarkar's algorithm and an interaction/prediction algorithm, respectively, are used to solve the model, the former for the large scale problems and the latter for the very large scale. With the help of the above-mentioned algorithms and HPP examples, Karmarkar's algorithm and the interaction/prediction algorithm are compared and analyzed, the results of which show that the proposed approaches are quite effective and suitable for both ‘push’ and ‘pull’ production.     

Materials requirement planning with a microcomputer

Materials requirement planning (MRP) has been implemented on equipment ranging from early EAM punchcard equipment to the largest mainframe computers. The availability of relatively capable microcomputers raises the possibility of MRP systems for small operations. A major obstacle is that the concepts underlying most MRP systems are such that both time and memory capability become critical. A system of three programs has been developed using a different computational concept. The “Gozinto” method is used for structuring bill of materials data, and matrix multiplication is used for data manipulation and report generation. The system is reasonably fast, and uses disc memory to alleviate memory constraints. Written in UCSD Pascal, it is usable in any microcomputer supporting that language that has two disc drives and a minimum of 56K of memory. The first program is the bill of materials processor, which receives bill of materials data input from the CRT and stores it on disc using any firm's part coding system. The bill of materials file is then reindexed to develop a triangular matrix. This matrix is then inverted to arrange the bill of materials data in “indented” form. The second “planning” program receives input from the CRT to develop a data base containing master schedule, inventory, order, lot size and other data. The matrix multiplication of the data base and the indented bill of materials is then done on a disc-to-disc basis, obviating the need for large working memory. This second program also provides for revision of the data base as the time periods progress. Results are printed by a third program that essentially despools the matrix products. Limited testing using data from a cooperating firm indicates usefulness with a minimal computer configuration. Extension to larger firms seems feasible with modest memory expansion.     

面向延迟制造的MRP动态调整方法研究

延迟制造要求对相同的在制品根据不同的客户需求进行工艺区分. 过程质量的不确定性使得传统物料需求计划(Material requirement planning, MRP)难以满足延迟区分的实时性要求. 本文简要介绍了面向延迟制造的物料需求计划改进方法, 提出了基于累计实时合格率的物料需求计划动态调整方法, 开发了实现算法. 应用案例表明: 该方法能够实时地根据各生产阶段的质量波动对物料需求计划进行动态调整, 制定合理的在制品工艺区分决策.