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Effects of Breakdown, Backlog and Rework on Replenishment Lot Size  [cached]
Tsu-Ming Yeh,Chia-Kuan Ting,Fan-Yun Pai,Jyh-Chau Yang
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: This study studies the effects of machine breakdown, backlog and rework on the replenishment lot size. In real-life manufacturing systems, random defective rate and breakdown of equipment are inevitable. When backlogging is permitted during a production run, a random machine failure may take place either in backlog filling stage or in inventory piling time; this study focuses on the former situation and considers all defective items produced are repairable through a rework process. The objective of this study is to determine the optimal run time that minimizes the long-run average production-inventory costs. The result can be directly applied to the practical production planning and control field to assist practitioner in production management cost reduction.
Economic production quantity models for imperfect product and service with rework  [PDF]
Allen H. Tai
Mathematics , 2012,
Abstract: When imperfect quality products are produced in a production process, rework may be performed to make them become serviceable. In an inventory system, items may deteriorate. Selling deteriorated items to customers will create negative impact on corporate image. In this paper, two economic production quantity (EPQ) models are proposed for deteriorating items with rework process. A single production-rework plant system and a system consists of $n$ production plants and one rework plant are considered. Approximated analytic results are obtained and numerical examples are provided to illustrate the solution procedure.
An EPQ Model with Imperfect Production Systems with Rework of Regular Production and Sales Return  [PDF]
C. Krishnamoorthi, S. Panayappan
American Journal of Operations Research (AJOR) , 2012, DOI: 10.4236/ajor.2012.22026
Abstract: The Economic Production Quantity (EPQ) model is commonly used by practitioners in the fields of production and inventory management to assist them in making decision on production lot size. The common assumptions in this model are that all units produced are perfect and shortages are not allowed. But, in real situation the defective items will be produced in each cycle of production and shortages and scrap are possible. These assumptions will underestimate the actual required quantity. Hence, the defective items can not be ignored in the production process. Rework process is necessary to convert those defective into finished goods. This study proposes EPQ model that incorporates both imperfect production quality and falsely not screening out a proportion of defects, thereby passing them on to customers, resulting in defect sales returns. To active this objective a suitable mathematical model is developed and the optimal production lot size which minimizes the total cost is derived. An illustrative example is provided and numerically verified. The validation of result in this model was coded in Microsoft Visual Basic 6.0.
Algebraic Improvement on Effects of Random Defective Rate and Imperfect Rework Process on Economic Production Quantity Model  [PDF]
Yung-Fu Huang
Journal of Applied Sciences , 2006,
Abstract: The present note studied the effect of random defective rate and imperfect rework process on the Economic Production Quantity (EPQ) model. They demonstrate that the optimal lot size can be solved algebraically and the expected inventory cost can be derived immediately as well. In this note, we will offer a simple algebraic approach to replace their algebraic skill to find the optimal solution under the expected annual cost minimized.
EPQ Model for Trended Demand with Rework and Random Preventive Machine Time  [PDF]
Nita H. Shah,Dushyantkumar G. Patel,Digeshkumar B. Shah
ISRN Operations Research , 2013, DOI: 10.1155/2013/485172
Abstract: Economic production quantity (EPQ) inventory model for trended demand has been analyzed with rework facility and stochastic preventive machine time. Due to the complexity of the model, search method is proposed to determine the best optimal solution. A numerical example and sensitivity analysis are carried out to validate the proposed model. From the sensitivity analysis, it is observed that the rate of change of demand has significant impact on the optimal inventory cost. The model is very sensitive to the production and demand rate. 1. Introduction An item that does not satisfy quality standards but can be attained after reprocess is termed as a recoverable item and the process is known as rework. It is observed that in an industrial sector, the rework reduced production cost and maintained quality standard of the item. Schrady [1] debated rework process. Khouja [2] formulated an economic lot-size and shipment policy by incorporating a fraction of defective items and direct rework. Koh et al. [3] and Dobos and Richter [4] discussed two production policies with options to order new products externally or recover old products. Chiu et al. [5] analyzed an imperfect rework process for EPQ model with repairable and scrapped items. Jamal et al. [6] advocated the policy for rework of defective items in the same cycle which was extended by Cárdenas-Barrón [7]. Widyadana and Wee [8] gave an analysis of these problems using an algebraic approach. Chiu [9] and Chiu et al. [10] discussed EPQ model by allowing shortages and considering service level constraint. Yoo et al. [11] discussed an EPQ model with imperfect production quality, imperfect inspection, and rework. Meller and Kim [12], Sheu and Chen [13] and Tsou and Chen [14] studied Variants of EPQ model with preventive maintenance. Abboud et al. [15] analyzed an economic order quantity model by considering machine unavailability owing to preventive maintenance and shortage. Chung et al. [16] extended the previous model to compute an economic production quantity for deteriorating inventory model with stochastic machine unavailable time and shortage. Wee and Widyadana [17] revisited the previous model incorporating rework. In this paper, we analyze an economic production quantity (EPQ) model with rework and random preventive maintenance time together when demand is increasing function of time. The consideration of random preventive maintenance time, rework, and trended demand in the model increases its applicability in the electronic and automobile industries. In this production system, produced items are
A joint lot-sizing and marketing model with reworks, scraps and imperfect products
Mohsen Fathollah Bayati,Morteza Rasti Barzoki,Seyed Reza Hejazi
International Journal of Industrial Engineering Computations , 2011,
Abstract: In this paper, we establish an economic production quantity (EPQ) based inventory model by considering various types of non-perfect products .We classify products in four groups of perfect, imperfect, defective but reworkable and non-reworkable defective items. The demand is a power function of price and marketing expenditure and production unit cost is considered to be a function of lot size. The objective of this paper is to determine lot size, marketing expenditure, selling price, set up cost and inventory holding cost, simultaneously. The problem is modeled as a nonlinear posynomial geometric programming and an optimal solution is derived. The implementation of the proposed method is demonstrated using a numerical example and the sensitivity analysis is also performed to study the behavior of the model.
Replenishment Decision Making with Permissible Shortage, Repairable Nonconforming Products and Random Equipment Failure  [cached]
Huei-Hsin Chang,Singa Wang Chiu,Yuan-Shyi Peter Chiu
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: This study is concerned with replenishment decision making with repairable nonconforming products, backordering and random equipment failure during production uptime. In real world manufacturing systems, due to different factors generation of nonconforming items and unexpected machine breakdown are inevitable. Also, in certain business environments various situations between vendor and buyer, the backordering of shortage stocks sometimes is permissible with extra cost involved. This study incorporates backlogging, random breakdown and rework into a production system, with the objective of determination of the optimal replenishment lot size and optimal level of backordering that minimizes the long-run average system costs. Mathematical modeling along with the renewal reward theorem is employed for deriving system cost function. Hessian matrix equations are used to prove its convexity. Research result can be directly adopted by practitioners in the production planning and control field to assist them in making their own robust production replenishment decision.
Examining Requirements Change Rework Effort: A Study  [PDF]
Bee Bee Chua,June Verner
Computer Science , 2010, DOI: 10.5121/ijsea.2010.1304
Abstract: Although software managers are generally good at new project estimation, their experience of scheduling rework tends to be poor. Inconsistent or incorrect effort estimation can increase the risk that the completion time for a project will be problematic. To continually alter software maintenance schedules during software maintenance is a daunting task. Our proposed framework, validated in a case study confirms that the variables resulting from requirements changes suffer from a number of problems, e.g., the coding used, end user involvement and user documentation. Our results clearly show a significant impact on rework effort as a result of unexpected errors that correlate with 1) weak characteristics and attributes as described in the program's source lines of code, especially in data declarations and data statements, 2) lack of communication between developers and users on a change effects, and 3) unavailability of user documentation. To keep rework effort under control, new criteria in change request forms are proposed. These criteria are shown in a proposed framework; the more case studies that are validated, the more reliable the result will be in determining the outcome of effort rework estimation.
Examining Requirements Change Rework Effort: A Study  [PDF]
Bee Bee Chua,June Verner
International Journal of Software Engineering & Applications , 2010,
Abstract: Although software managers are generally good at new project estimation, their experience of schedulingrework tends to be poor. Inconsistent or incorrect effort estimation can increase the risk that the completiontime for a project will be problematic. To continually alter software maintenance schedules during softwaremaintenance is a daunting task. Our proposed framework, validated in a case study confirms that the variablesresulting from requirements changes suffer from a number of problems, e.g., the coding used, end userinvolvement and user documentation. Our results clearly show a significant impact on rework effort as a resultof unexpected errors that correlate with 1) weak characteristics and attributes as described in the program’ssource lines of code, especially in data declarations and data statements, 2) lack of communication betweendevelopers and users on a change effects, and 3) unavailability of user documentation. To keep rework effortunder control, new criteria in change request forms are proposed. These criteria are shown in a proposedframework; the more case studies that are validated, the more reliable the result will be in determining theoutcome of effort rework estimation.
Decision Taking versus Promise Issuing  [PDF]
Jan A. Bergstra
Computer Science , 2013,
Abstract: An alignment is developed between the terminology of outcome oriented decision taking and a terminology for promise issuing. Differences and correspondences are investigated between the concepts of decision and promise. For decision taking, two forms are distinguished: the external outcome delivering form and internalized decision taking. Internalized decision taking is brought in connection with Marc Slors' theory of self-programming. Examples are produced for decisions and promises in four different several settings each connected with software technology: instruction sequence effectuation, informational money transfer, budget announcement, and division by zero.
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