Complexity and uncertainty of materials procurement in assembly situations (original) (raw)

Supply management in assembly systems

Naval Research Logistics, 1993

We consider the case when n components are needed to assemble a given product. Components are provided by suppliers, and the period between the order time and the time a component is available (i.e., the lead time) is a random variable with a known distribution. The due date for the assembled product is also known. The costs to be taken into account are the inventory costs of the components and the backlogging cost of the assembled product. We propose an iterative algorithm which leads to the optimal order instants of the components. 0 1993 John Wiley & Sons, Inc.

Contract Assembly: Dealing with Combined Supply Lead Time and Demand Quantity Uncertainty

Manufacturing & Service Operations Management, 2000

W e consider a problem faced by a contract assembler that both assembles finished goods and procures the associated component parts for one of its major customers. Because of rapid changes in technology and ongoing engineering changes, all parts subject to obsolescence are purchased only for the current customer order. The procurement lead times of the components are random. Moreover, although the order for the finished product has a defined due date, the contract allows the customer to change the order quantity. Consequently, the assembler also faces a random demand. The assembler must determine how much to order and when to order each component part. The objective is to minimize the total expected cost, including the cost of holding components prior to their assembly, penalties for tardiness visa-vis the assembly due date, and overage and underage costs in satisfying the demand quantity. We present some structural results and discuss insights regarding optimal policies. We also present several simple heuristic policies and compare them to optimal policies. Computational results indicate that ignoring lead time variability can be costly, but relatively simple heuristics that consider lead time variability perform quite well.

An intelligent approach for managing materials purchasing in the RMC industry

The 25th International Symposium on Automation and Robotics in Construction. ISARC-2008, 2008

A model for comparing the inventory costs of purchasing under the economic order quantity (EOQ) system and the just-intime (JIT) order purchasing system in existing literature concluded that JIT purchasing was virtually always the preferable inventory ordering system especially at high level of annual demand. By expanding the classical EOQ model, this paper shows that it is possible for the EOQ system to be more cost effective than the JIT system once the inventory demand approaches the EOQ-JIT cost indifference point. The intelligent agent paradigm, a natural fit to solve dynamic materials control problem, however has seldom been deployed in construction material management. Based on the EOQ-JIT cost indifference point function, an alternative agent based inventory management system is thus developed. A case study demonstrates how the equation affects the purchasing approach of a material.

An integration of assembly planning by design into supply chain planning

The International Journal of Advanced Manufacturing Technology, 2013

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Supply chain models for an assembly system with preprocessing of raw materials

European Journal of Operational Research, 2007

An assembly line that procures raw materials from outside suppliers and processes the materials into finished products is considered in this research. An ordering policy is proposed for raw materials to meet the requirement of a production facility, which, in turn, must deliver finish products i n a fixed quantity at a fixed time interval to the outside buyers. Two different types of raw materials, 'unfinished' and 'ready-to-use', are procured for the manufacturing system. The 'unfinished raw materials' are turned into 'processed raw materials' after preprocessing. In the assembly line, the 'processed raw materials' and the 'ready raw materials' are assembled to convert into the final products. A cost model is developed to aggregate the total costs of raw materials, Work-in-process, and finished goods inventory. Based on the product design and manufacturing requirement a relationship is established between the raw materials and the finished products at different stages of production. A non-linear integer-programming model is developed to determine the optimal ordering policies for procurement of raw materials, and shipment of assembly product, which ultimately minimize the total costs of the model. Numerical examples are presented to demonstrate the solution technique. Sensitivity analysis is performed to show the effects of the parameters on the total cost model. Future research direction is suggested for further improvement of the existing results.

Assemble-to-order manufacturing: Implications for materials management

Journal of Operations Management, 1984

A company's manufacturing is often characterized as either make-to-stock (MTS), make-to-order (MTO), or assemble-to-order (ATO). This classification relates to the degree of interaction between the ~chnoio~~ core and the market, with MTS involving the least amount of interaction and MT0 the highest degree of contact. AT0 represents a hybrid manufa~u~ng strategy for which parts and subassemblies are made according to forecasts while the final mmbly of the products is delayed until customer orders have been received. It is evident that each manufacturing philosophy has strategic as well as operational implications.

A conceptual model for demand management in the assemble-to-order environment

Journal of Operations Management, 1990

The term demand management encompasses the activities required to accept customer orders and promise them productive capacity. This activity is central to effective manufacturing planning and control. The popularity of just-in-time systems suggests that manufacturers are steadily losing authority for establishing order delivery dates, further confounding the demand management process. No reported research has suggested how this process can be performed.

IRJET- Comparison of Material Procurement Methods of a Construction Projects-Case Study

IRJET, 2020

Procurement Process is the process required to supply equipment, materials and other resources required to carry out a project. This process usually involves sub-processes such as acquisition, purchasing, logistics, monitoring, quality assurance and contract administration. An important factor that affects the performance of construction projects is the improper handling of materials during site activities. This an effort to analyze the Process analysis of material Procurement management by generating strategies to improve the procurement process in commercial projects. To avoid delays mainly the material planning to be carried out on time with the relevant material details material approval, material lead time, and material delivery and to be properly tracked. One or combination of Information and Communication Technology helps in effective management of materials at various stages of construction. Application of ICT enables the maximum accuracy of estimation of requirements and it is made sure that required amount of material is procured at the project site avoiding the wastages and difficulties in storages etc.

Review and challenges for the remanufacturing assembly quality with uncertainty

Green Manufacturing Open, 2023

Remanufacturing businesses have difficulty in competing and expanding due to the unpredictable quality and performance of remanufactured products. It has turned into a problem area and a bottleneck for the growth of the remanufacturing sector. The control and management of remanufactured assembly quality (RAQ) is considered one of the key factors affecting the quality of remanufactured products. By reviewing existing literature, we have found that in remanufacturing assembly systems, the uncertainty of remanufacturing components, the volatility of remanufacturing assembly processes, the complexity of assembly control, and the diversity of assembly schemes are the main reasons for the difficulty in ensuring assembly quality. However, existing literature lacks research on data management, evolutionary mechanisms of RAQ, and multivariate control. To improve the stability of RAQ and improve the quality of remanufactured products, we propose the construction of an intelligent reasoning mode for precise RAQ control and a tailored, intelligent control method for individual components, providing support for the intelligent control of remanufactured assembly functional modules. This study provides a basis for implementing high-performance assembly technology for remanufactured products. Our findings should encourage the industry's modernization for remanufacturing.