MODELING SCRAP SOURCING DECISIONS GIVEN UNCERTAIN DEMAND (original) (raw)
Modeling methods for managing raw material compositional uncertainty in alloy production
Resources, Conservation and Recycling, 2007
Operational uncertainties create disincentives for use of recycled materials in metal alloy production. One that greatly influences remelter batch optimization is variation in the raw material composition, particularly for secondary materials. Currently, to accommodate compositional variation, firms commonly set production targets well inside the window of compositional specification required for performance reasons. Window narrowing, while effective, does not make use of statistical sampling data, leading to sub-optimal usage of recycled materials. This paper explores the use of a chance-constrained optimization method, which allows explicit consideration of statistical information on composition. The framework and a case study of cast and wrought production with available scrap materials are presented. Results show that it is possible to increase the use of recycled material without compromising the likelihood of batch errors, when using this method compared to conventional window narrowing. This benefit of the chance-constrained method grows with increase in compositional uncertainty and is driven by scrap portfolio diversification.
The production-inventory model with imperfect, rework, and scrap items under stochastic demand
International Journal of Advances in Applied Sciences (IJAAS), 2024
Inventory is crucial in maintaining a smooth production process and meeting consumer demand for manufacturing companies. This research focuses on production problems involving defects, rework, and scrap items in stochastic demand. This research aims to develop a production-availability model by minimizing the expectation of total cost (ETC). The model includes four main decision variables, namely production quantity (Q), safety factor (k), production rate (P), and rework rate (P1). This research uses the Aquila optimizer algorithm to optimize the objective function. It compares with the heuristic procedure and Harris Hawk optimization algorithm. The results showed that the Aquila optimizer algorithm successfully optimized the production-availability problem. A comparison between algorithms indicates that the Aquila optimizer algorithm performs equivalently to the Harris Hawk optimization algorithm and outperforms the heuristic procedure. Sensitivity analysis shows that increasing demand uncertainty increases ETC and k. At the same time, it can decrease Q.
Optimizing Scrap Management in Production Planning Processes
International Journal of Computer Trends and Technology, 2023
Scrap management is an important aspect of any manufacturing process, as it can significantly impact costs, inventory, and product quality. SAP, one of the leading enterprise software providers, offers various solutions for managing scrap, including assembly scrap, component scrap, and operation scrap. This paper provides a comprehensive review of these three types of scrap handling in SAP and analyzes their effects on manufacturing processes. The paper begins by outlining the differences between assembly scrap, component scrap, and operation scrap in SAP. It then examines various strategies for handling these types of scrap, including manual data entry, automated data collection, and integration with inventory management and production planning. The paper also discusses the benefits and drawbacks of each strategy, such as increased data accuracy, reduced inventory costs, and improved production planning. The paper draws on published research articles, case studies, and industry reports to analyse the effects of using these strategies. The analysis focuses on the impact of scrap handling on key performance indicators (KPIs) such as cost, quality, and inventory levels. The paper highlights how different strategies can impact these KPIs and identifies best practices for optimizing scrap management in SAP. Overall, this review paper provides valuable insights into the various ways to handle scrap in SAP and the effects of using these strategies. By examining assembly scrap, component scrap, and operation scrap handling in detail, this paper serves as a useful resource for companies seeking to improve their scrap management capabilities in SAP.
Quality control planning to prevent excessive scrap production
Journal of Manufacturing Systems, 2014
This paper presents a risk-based approach for quality control planning of complex discrete manufacturing processes, to prevent massive scraps to occur. An analytical model is developed to optimize the quality control plan (QCP) subject to inspection capacity limitation and risk exposure objectives. The problem is then formulated as a constrained capacity allocation problem. A dedicated heuristic that solves a simplified instance of an industrial case study, from semiconductor manufacturing, is presented to provide insights into the applicability and the operational use of the approach and its potential gains in terms of risk exposure reduction. The main advancement resulting from this work is the proposal of a model of quality control allocation and an understandable algorithm to prevent the production of excessive amounts of scrap. The industrial illustration shows a decrease in potential losses by a factor of 3.
Complexity and uncertainty of materials procurement in assembly situations
International Journal of Production Economics, 1996
In this paper, the complexity and uncertainty in the process of obtaining materials from outside suppliers is studied. A set of explorative case studies is used to examine this uncertainty and complexity experienced in assembly situations as well as the control mechanisms and control variety that are developed to meet this complexity and uncertainty. A framework is introduced for materials procurement and used to establish a number of characteristics which should be taken into account in designing control in different procurement situations. Additionally, a general control structure is developed in order to describe and compare the five companies with respect to the way in which the material flow is controlled.
Research Journal of Applied Sciences, Engineering and Technology, 2014
In a recent study, employed a mathematical modeling and conventional optimization technique to determine the optimal production-shipment policy for a single-producer multi-retailer integrated inventory system with scrap and an improved product distribution policy. This study replaces their optimization process of using differential calculus with an algebraic derivation. Such a simplified approach enables practitioners, who may have insufficient knowledge of calculus, to manage with ease the real world supply-chain systems.
Inventory Planning For WoOden Pallet Raw Material in Probabilistic Condition
International Journal of Engineering Research & Advanced Technology (IJERAT), 2022
Wooden pallet industry often experienced either shortage or exceed of raw materials which makes the industry suffer for a significant losses due to the company's inability to provide products to fulfill the demand. This deficiency is due to the fact that the company did not have a proper inventory planning of raw material required for the production, as a consequence the company often has to buy the raw material at a higher price in an urgent condition. In order to make a cost efficiency, the activities of purchase and usage of this raw materials need to be planned at the best possible cost so that companies can avoid unnecessary waste of operational costs. With the unpredicted of raw material resources used by the company and quantity of consumer demand, inventory policy planning is needed to determine the most economical quantity required and the time for the company to place the order in these probabilistic conditions.
Models for production planning under uncertainty: A review
International Journal of Production Economics, 2006
The consideration of uncertainty in manufacturing systems supposes a great advance. Models for production planning which do not recognize the uncertainty can be expected to generate inferior planning decisions as compared to models that explicitly account for the uncertainty. This paper reviews some of the existing literature of production planning under uncertainty. The research objective is to provide the reader with a starting point about uncertainty modelling in production planning problems aimed at production management researchers. The literature review that we compiled consists of 87 citations from 1983 to 2004. A classification scheme for models for production planning under uncertainty is defined. r (J. Mula). Analytical models [3] 3. Material requirement planning Conceptual models [9] Analytical models [6] Artificial intelligence models [4] Simulation models [10] 4. Capacity planning Analytical models [4] Simulation models [1] 5. Manufacturing resource planning Analytical models [7] Artificial intelligence models [5] Simulation models [2] 6. Inventory management Analytical models [10] Artificial intelligence models [5] 7. Supply chain planning Conceptual models [1] Analytical models [5] Artificial intelligence models [5] J. Mula et al. / Int. J. Production Economics 103 (2006) 271-285 272
American Journal of Computational Mathematics, 2011
This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal productionshipment policies. A simpler form for computing long-run average cost for such a vendor-buyer integrated EPQ problem is also provided.
Sourcing with random yields and stochastic demand: A newsvendor approach
Computers & Operations Research, 2007
We studied a supplier selection problem, where a buyer, while facing random demand, is to decide ordering quantities from a set of suppliers with different yields and prices. We provided the mathematical formulation for the buyer's profit maximization problem and proposed a solution method based on a combination of the active set method and the Newton search procedure. Our computational study shows that the proposed method can solve the problem efficiently, and is able to generate interesting and insightful results that lead us to various managerial implications.