Download Free Production And Inventory Control Of A Multi Item Multi Stage Manufacturing System Book in PDF and EPUB Free Download. You can read online Production And Inventory Control Of A Multi Item Multi Stage Manufacturing System and write the review.

The project work presented in this thesis has proposed solutions related to the control of production and work-in-process inventory in a multi-item multi-stage manufacturing system. A suitable base-stock inventory control policy is recommended to ensure that the desired service levels are maintained between production stages and for the final customers. Concept of coupling the production lines though coupling-stock under suitable assumptions is then introduced to reduce the stock levels at certain consecutive production stages. A framework for demand seasonality and characteristic analysis is also established to enable the inventory control policy to respond to seasonal variations. Monte Carlo simulation was performed on a model of chain of production stages controlled under base-stock policy for the verification of results and to study the effects of stock-outs on base-stock levels. The results of simulation study showed that overall system performance is satisfactory and desired service levels were achieved. Simulation work was also carried out to validate the line coupling concept and its performance under certain conditions. A novel Kanban based visual management system design, which is aligned with the requirements of inventory control policy, along with the material transfer batch sizes between production stages is proposed to facilitate the implementation of inventory control policy. Furthermore, capacitated shipment planning approach is proposed and implemented in form of a spreadsheet-based interface to aid planning personnel in shipment planning under the constraints provided by the inventory control policy.
This paper treats a two-echelon inventory system. The higher echelon is a single location reffered to as the depot, which places orders for supply of a single com modity. The lower echelon consists of several points, called the retailers, which are supplied by shipments from the depot, and at which random demands for the item occur. Stocks are reviewed and decisions are made periodically. Orders and/or shipments may each require a fixed lead time before reaching their respective desti nations. Section II gives a short literature review of distribution research. Section III introduces the multi-echelon distribution system together with the underlying as sumptions and gives a description of how this problem can be viewed as a Markovian Decision Process. Section IV discusses the concept of cost modifications in a distribution context. Section V presents the test-examples together with their optimal solutions and also gives the characteristic properties of these optimal solutions. These properties then will be used in section VI to give adapted ver sions of various heuristics which were used in assembly experiments previously and which will be tested against the test-examples.
The project is conducted in a multi-item-multi-stage manufacturing system with high volume products. The objectives are to optimize the inventory structure and improve production scheduling process. The stock building plan is studied carefully to understand the demand seasonality characteristics and the planning guidelines that the factory is currently following. A new base stock policy is introduced to the 5 focused production stages to establish a demand driven system with controlled inventory and new rules to guide the daily production. The line coupling concept is also added to further refine the inventory structure. After that, the production leveling method is employed to help reduce the variation of daily production targets. Finally, a Kanban system is designed to facilitate the demand driven manufacturing under the operation of the new base stock policy. With the appropriate inventory control and production scheduling policy, the overall inventory level in the factory is reduced by 61% based on calculation, leading to a savings of 70% of the total inventory cost. Moreover, the establishment of Kanban system has simplified the daily manufacturing activity on the operation level and helped the factory become a lean manufacturer.
Authored by a team of experts, the new edition of this bestseller presents practical techniques for managing inventory and production throughout supply chains. It covers the current context of inventory and production management, replenishment systems for managing individual inventories within a firm, managing inventory in multiple locations and firms, and production management. The book presents sophisticated concepts and solutions with an eye towards today’s economy of global demand, cost-saving, and rapid cycles. It explains how to decrease working capital and how to deal with coordinating chains across boundaries.
This book discusses inventory models for determining optimal ordering policies using various optimization techniques, genetic algorithms, and data mining concepts. It also provides sensitivity analyses for the models’ robustness. It presents a collection of mathematical models that deal with real industry scenarios. All mathematical model solutions are provided with the help of various optimization techniques to determine optimal ordering policy. The book offers a range of perspectives on the implementation of optimization techniques, inflation, trade credit financing, fuzzy systems, human error, learning in production, inspection, green supply chains, closed supply chains, reworks, game theory approaches, genetic algorithms, and data mining, as well as research on big data applications for inventory management and control. Starting from deterministic inventory models, the book moves towards advanced inventory models. The content is divided into eight major sections: inventory control and management – inventory models with trade credit financing for imperfect quality items; environmental impact on ordering policies; impact of learning on the supply chain models; EOQ models considering warehousing; optimal ordering policies with data mining and PSO techniques; supply chain models in fuzzy environments; optimal production models for multi-items and multi-retailers; and a marketing model to understand buying behaviour. Given its scope, the book offers a valuable resource for practitioners, instructors, students and researchers alike. It also offers essential insights to help retailers/managers improve business functions and make more accurate and realistic decisions.
Quantitativeapproachesforsolvingproductionplanningandinventorymanagement problems in industry have gained growing importance in the past years. Due to the increasinguse of AdvancedPlanningSystems, a widespreadpracticalapplicationof the sophisticated optimization models and algorithms developed by the Production Management and Operations Research community now seem within reach. The possibility that productscan be replaced by certain substitute productsexists in various application areas of production planning and inventory management. Substitutions can be useful for a number of reasons, among others to circ- vent production and supply bottlenecks and disruptions, increase the service level, reduce setup costs and times, and lower inventories and thereby decrease ca- tal lockup. Considering the current trend in industry towards shorter product life cycles and greater product variety, the importance of substitutions appears likely to grow. Closely related to substitutions are ?exible bills-of-materials and recipes in multi-level production systems. However, so far, the aspect of substitutions has not attracted much attention in academic literature. Existing lot-sizing models matching complex requirements of industrial optimization problems (e.g., constrained capacities, sequence-dependent setups, multiple resources) such as the Capacitated Lot-Sizing Problem with Sequence-Dependent Setups (CLSD) and the General Lot-Sizing and Scheduling Problem for Multiple Production Stages (GLSPMS) do not feature in substitution options.
As markets become more dynamic and competitive, companies must reconsider how they view inventory and make changes to their production and inventory systems. They must begin to think outside the classical box and develop a new paradigm of inventory management. Exploring the trend away from classical models based on economic order quantities to depe
Handbook