Quality control planning to prevent excessive scrap production (original) (raw)
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Optimized design of control plans based on risk exposure and resources capabilities
2010
In this paper, we present a coherent method for quality control planning that tackles the limitations of traditional approaches when applied to an advanced high-mix fab like semiconductor manufacturing environment. The proposed approach consists of two stages and takes into account both the risk exposure, expressed in terms of the number of products potentially lost, and resources capabilities (process and measurement tools).
Journal of Intelligent Manufacturing, 2014
Semiconductor manufacturing processes are very long and complex, needing several hundreds of individual steps to produce the final product (chip). In this context, the early detection of process excursions or product defects is very important to avoid massive potential losses. Metrology is thus a key step in the fabrication line. Whereas a 100 % inspection rate would be ideal in theory, the cost of the metrology devices and cycle time losses due to these measurements would completely inhibit such an approach. On another hand, the skipping of some measurements is risky for quality assurance and processing machine reliability. The purpose is to define an optimized quality control plan that reduces the required capacity of control while maintaining enough trust in quality controls. The method adopted by this research is to employ a multi-objective genetic algorithm to define the optimized control plan able to reduce the used metrology capacity without increasing risk level. Early results based on one month of real historical data computation reveal a possible reallocation of controls with a decrease by more than 15 % of metrology capacity while also reducing the risk
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.
A cost minimisation model for joint production and maintenance planning under quality constraints
In this paper, integrated planning of production, imperfect maintenance and process inspections in a multi-machine system is investigated. This system consists of parallel machines which deteriorate with time and they may shift from a primarily in-control state to a degraded state with a higher defective rate or to a failed state. Maintenance scheduling corresponds to a discrete time age-based imperfect maintenance with a large number of maintenance alternatives. Process inspections are considered to detect the current state of the system. Detecting a deteriorated condition initiates the quality check of the related sub-lots, rework of defective items and a process adjustment that brings the machine in its normal conditions. Production planning includes a capacitated lot-sizing problem with multiple products. We propose a joint approach that coordinates the decisions of the three functions, where the objective function minimises the total cost. Evaluation of costs and interacting factors is presented and two heuristic methods are proposed to solve the problem. The results of the joint model are compared to a non-integrated method and a sensitivity analysis is conducted. 1. Introduction In the competitive business environment of this era, organisations are seeking strategies to improve the quality and system's reliability while reducing the costs. Performance of a system and productivity of its functions are highly related to the coordination and cooperation of the subsystems. Production planning, maintenance scheduling and quality systems are the three functions of manufacturing systems with different goals defined on shared subjects. Despite the conventional approaches in the literature dealing separately with these functions, integrated strategy is an appropriate policy to handle the interactions between them. Lot-sizing decision as a well-studied problem is the determination of production levels, such that the total cost is minimised (Karimi, Fatemi Ghomia, and Wilson 2003). This type of problems arises in a wide range of industries and its complexity corresponds to the problem features such as the number of products, levels and machines, planning horizon, structure of setups , processing times, rework process and customer demands. In the capacitated lot-sizing problem (CLSP), the production levels are restricted for example to the available time and this latter is influenced by maintenance operations and random failures. The well-known Economic Production Quantity (EPQ) model is a subset of CLSP problems. Dohi, Okamura, and Osaki (2001) stated that in the presence of quality deterioration and machine failures, the classic EPQ model losses its usefulness and the uncertainty should be incorporated in the model. The general objective of preventive maintenance (PM) is to maximise the machine availability, or to minimise the system cost (Nourelfath, Ben-Daya, and Nahas 2016). Among the maintenance policies, the age-based maintenance (a subset of the condition-based PM) is an efficient approach employed in several papers (Ben-Daya 2002; El-Ferik 2008; Lu, Zhou, and Li 2016) to link the PM decisions to production or quality plans. PM improves the machine availability and reliability by reducing the rate of failures or increases the quality by enhancing their function. Quality control tools and process inspections are efficiently used to evaluate the hidden state of a system and to detect the process variations. Certain types of deteriorations may originate from internal resources and inspections are employed to signal the need for a maintenance or a process adjustment. Duncan (1956) proposed the economic design of a quality control chart to maximise the unit profit per time in a single machine system. In his model, the optimal determination of the sample size, length of the sampling interval and the control limits of an x-chart are addressed.
A NEW MODEL FOR PRODUCTION, INSPECTION, AND MAINTENANCE: MODEL VALIDATION AND CASE STUDY
Journal Paper, 2020
A model is developed to integrate production planning, preventive maintenance, and process/product quality inspection decisions. The integrated model objective is to minimize the total costs of the three decisions that are subjected to constraints of production availability, preventive maintenance economical limitations, and system reliability constraints. Genetic Algorithms and Mixed Integer Linear Program are utilized to solve such complicated problems with constraints considered. An extensive literature review has been presented. The integration of the production, preventive maintenance, and quality decisions in one integrated model is rare so that further investigations and real case study applications in the industry fields are needed. The proposed model and solution method are compared and validated with four models and methodologies from literature. A case study demonstrates the significant improvements of the model results on a real practical industrial application, which also validates the proposed model.
Controlling defective items in a complex multi-phase manufacturing system
RAIRO - Operations Research, 2022
In manufacturing systems, defective items are produced for machine drift and error. Usually, an imperfect production rate is random, and if the items are not reworked, these are considered trash and harm the environment. The proposed model aims to reduce waste by reworking defective products and maximizing profit. For profit maximization or overall cost minimization of the manufacturing system, setup cost has significant. A discrete investment for each phase is introduced with an inequality investment constraint for reducing the setup cost. Selling price-dependent demand is trained for more generalized applications for various industries. The proposed model is a multi-phase manufacturing system with optimum batch size, selling price, and investment with an irregular, imperfect production rate. Defects are detected at the first inspection, and the reworked items are checked if the reworked items are all non-defective in the second inspection. The model conducts a two-stage inspection...
Production risk management in the foundry
Naukovij vìsnik Nacìonalʹnogo gìrničogo unìversitetu, 2020
PRoDuCtIoN RISK MANAGeMeNt IN the fouNDRy Purpose. Improving the efficiency of production risk management of a machinebuilding enterprise unit by: 1) improving the methodology of analysis of existing risks; 2) developing a costoptimization program for risk management. Methodology. The study used general scientific and specific research methods: analysis, generalization of scientific experience; risk and hazard assessment was carried out using the method of structured assessment; in solving the problem of cost optimization, the model of "knapsack problem" was used. findings. Since production risk management is related to the material costs of the enterprise for occupational safety measures, improving the effectiveness of risk management involves consistently using qualitative and quantitative assessments. The method ology was improved, the dangerous factors were identified and analyzed; the task of optimizing costs in risk management was set and solved. originality. The risk management approach is to use an advanced approach to evaluate and use the optimization model. Meth odological approaches to risk assessment have been further developed which include the calculation of not only the probability of occurrence. For the first time, to optimize the costs for occupational safety measures in the machinebuilding enterprise unit, the "knapsack problem" was used, which allows reducing the amount of risk to an acceptable level. Practical value. The results of the study are embodied in a specific methodology, the use of which allows the optimal way to manage risks in the enterprise unit.
Quality and Risk Management in Industrial Production Systems: A Literature Review
Bulletin of the Polytechnic Institute of Iași. Machine constructions Section
Nowadays quality management and specific tools can represent a challenge in SMEs (small and medium enterprises). To assure the expected quality of the products, SPC (statistical process control) combined with industry 4.0 specifics offer instantaneous responses and triggers for needed actions. Therefore, risk analyses are used as enablers for quality-oriented behaviour, and risk mitigation and identification, together with collected data, represent a comprehensive system that leads enterprises to achieve the expected performance level needed to remain competitive in the market. In addition, risk management and quality management cannot be treated without looking at the maintenance activities and policies which can have a considerable impact on those two. This paper provides a comprehensive literature review of the papers from the quality management sector and articles where risk management and maintenance are seen as facilitators for quality improvement with an impact on the perform...
Continuous Sampling Plan in Preventing Defects with Risk Evaluation in Production and Sales System
International Journal of Computer Applications, 2015
This paper studies a continuous sampling plan in preventing entries of defective products produced for sales using queueing theory methods. The sampling plan considered here has three inspection modes. All the products are inspected in mode I and in modes II and III the products are inspected with some probability c ≥ 0 and d > 0 respectively in the modes in order to avoid high cost of inspecting all products produced. Matrix methods are used for studying the stock level probabilities and various performance and risk measures including the rate of entry of defectives, expected defective products in the stock, standard deviation and the coefficient of variation are presented. Stationary stock level probabilities are derived using iterated rate matrix. Two special cases with c > 0 and d=1 and with c = 0 and d > 0 are considered. Numerical cases are treated to note the significance of the continuous sampling plan in reducing the entry rates. The expected defective products in the stock for sales and all the risk measures are listed and discussed.
Mathematical modelling of a robust inspection process plan: Taguchi and Monte Carlo methods
International Journal of Production Research, 2014
This study develops a new optimisation framework for process inspection planning of a manufacturing system with multiple quality characteristics, in which the proposed framework is based on a mixed-integer mathematical programming (MILP) model. Due to the stochastic nature of production processes and since their production processes are sensitive to manufacturing variations; a proportion of products do not conform the design specifications. A common source of these variations is misadjustment of each operation that leads to a higher number of scraps. Therefore, uncertainty in misadjustment is taken into account in this study. A twofold decision is made on the subject that which quality characteristic needs what kind of inspection, and the time this inspection should be performed. To cope with the introduced uncertainty, two robust optimisation methods are developed based on Taguchi and Monte Carlo methods. Furthermore, a genetic algorithm is applied to the problem to obtain near-optimal solutions. To validate the proposed model and solution approach, several numerical experiments are done on a real industrial case. Finally, the conclusion is provided.