Daily planning and scheduling system for the EDS process in a semiconductor manufacturing facility

For the past fifteen years, formalized procedures for economic planning have been the subject of intensive research. Underlying much of this research has been the analogy between planning procedures and decomposition algorithms from mathematical programming. Some authors, e.g. Baumol & Fabian (1964) and Burton et al. (1974), have interpreted certain decomposition algorithms as models of decentralized planning. Other authors, e.g. Jennergren (1971), have stated a planning problem and then gone on to find a decomposition algorithm which could serve as a procedure for solving their problem. Still other authors have constructed new planning procedures drawing on constructs and concepts from mathematical programming; see e.g. Rasmusen (1974), Malinvaud (1967) and Weitzman (1970). For recent surveys of planning procedures, see Heal (1973), Hurwicz (1973) and Ruefli (1974). The procedure outlined by Weitzman (1970) is generally regarded as attrac. tive from a planning point of view; see, e.g. Portes (1971). For one thing (and as distinguished from many other proposals) it is not too dissimilar from procedures actually used in economic systems, in particular as regards information flows between organizational units participating in the planning process. Although the procedure suggested by Weitzman appears to be promising for actual planning problems, it has some limitations. These are due to the fact that the procedure cannot be used in connection with (a) joint productions and (b) non-negative constraints, and that the central unit's estimate of the production set must contain the production set. That (a) and (b) really restrict the application of the procedure is obvious.

The daily production planning of sawmills is a critical task in pursuing the optimal exploitation of forest resources. Production planning determines which logs are to be processed, taking into account their characteristics with the aim of satisfying the demand for final products. Logs are turned into lumber when they are cut according to a set of available cutting patterns (CPs). The development of efficient production planning is a key factor in improving the productivity of sawmills, and mathematical modeling is a suitable technique to achieve this objective. In this paper, a mixed integer linear programming (MILP) model for optimal daily production planning in sawmills is proposed. The model involves a set of CPs for each type of log, which is obtained through an exhaustive algorithm, attaining all possible feasible CPs. The proposed approach determines the optimal number of logs of each type to be cut, the selected CPs to be used, material inventory, demand fulfillment, and other industrial and commercial issues with the objective of maximizing the firm’s benefit, in reasonable computational time, considering the size of the problem.

Construction and development of the Grasberg Block Cave (GBC) mine continues to progress, with undercutting commencing in late 2018.As an experienced operator of block cave mines, PT Freeport Indonesia (PTFI) works to improve the planning and execution of undercutting.The GBC mine, with its large size and complex geotechnical conditions, requires increased focus on initiating and sustaining caving.For the past two years, PTFI has worked on developing a software tool for detailed undercut planning.The tool utilises cave management rules, the geologic block model, and ring shapes to produce detailed tonnage and grade schedules.Additionally, further analytical processing of the tool's output data allows examination of the feasibility and required resources to implement the undercutting plan.As a constraint-based scheduling application, the tool provides a high degree of flexibility in adapting quickly to changing assumptions.Factors affecting GBC undercutting include high tonnage rates, mine development resources, and variable rock mass conditions.Of primary concern, with production targets between 130,000 and 160,000 tpd, drawbells must open at a sufficient pace to achieve acceptable caving production ramp-up and then maintain throughput targets.Detailed undercut scheduling alleviates those concerns by optimising production block start dates, caving rules, and ring designs, to drive cave production with an achievable drawbelling rate.These detailed schedules also enable vetting of mine development plans, construction plans, and resource requirements.The GBC geotechnical environment requires undercutting strategies to adapt accordingly.Poor rock mass conditions, large panel boundaries, and high-stress conditions all affect undercut start points, caving directions, and other design decisions.The ability to produce realistic, detailed schedules enables further study of the impacts with 3D numerical modelling.Results from numerical modelling have helped refine not only the caving strategy, but also the overall mine design.The importance of the undercutting plan for successful caving of the large footprint, high tonnage rate GBC mine remains a priority.In conjunction with the geotechnical engineers and operations personnel, the mine planning team utilises the newly developed undercut planning tool to adapt and improve undercutting plans as more informed data becomes available.The geotechnical and operational challenges to mining the GBC necessitate the methods and approach to planning discussed in this paper.

The management of operating rooms (ORs) is a complex process which requires an effective organizational scheme. In order to amore convinient allocation of resources a rigorous monitoring plan is needed to ensure operating rooms performances. All the necessary actions should be taken to improve the quality of the planning and scheduling procedure. Between April-December, 2016 an organizational analysis has been carried out on the performances of the A.O. S. Camillo-Forlanini Hospital Operating Block applying the "process management" approach to the ORs efficiency. The project involved two different surgical areas of the same operating block the multi-specialist and elective surgery and cardio-vascular surgery . The analyses of the processes was made through the product, patient and safety approach and from different points of view: the "asis", process and stakeholder perspectives. Descriptive statistics was used to process raw data and Student's t-distribution was used to assess the difference between the two means (significant p value ˂0,05). The Coefficient of Variation (CV) was used to describe the variabilityamong data. The asis approach allowed us to describe the ORs inbound activities. For both operating block the most demanding weekly commitments in terms of time turned out to be the inventory management procedures of controlling and stocking medicines, general medical supplies and instruments (130[DS=±14] for BOE and 30[DS=±18] for CCH. The average time spent on preparing the operating room, separately calculated starting from the first surgical case, was of 27 minutes (SD=± 17) while for the following surgical procedures preparation time decreased to 15 minutes (SD= ± 10), which highlighted a meaningful difference of 12 minutes. A great variability was registered in CCH due to the unpredictability of these operations (CV 82%). The stakeholders' perspective revealed a reasonable level of satisfaction among nurses and surgeons (2.9 vs 2.3, respectively) and in anesthesiologist (2.8-BOE vs 2.4 CCH).Being brought to the surgical suite from an "external Unit" seems to have negatively influenced the patient's perception: preparation time turned out to be significantly lower for CCH patients rather than BOE ones (p˂0,001).The results of the safety procedure approach highlighted a moderate criticality in terms of cleaning up time and delay in the starting time of the first surgical case. More effort should be made to avoid any slowdown during the whole process. It is advisable to implement a lean system that may improve efficiency and quality of the service to reduce wastes and unproductive times. This would inevitably generate a more positive outcomes.

Full-scale quantum computers require the integration of millions of qubits, and the potential of using industrial semiconductor manufacturing to meet this need has driven the development of quantum computing in silicon quantum dots. However, fabrication has so far relied on electron-beam lithography and, with a few exceptions, conventional lift-off processes that suffer from low yield and poor uniformity. Here we report quantum dots that are hosted at a 28Si/28SiO2 interface and fabricated in a 300 mm semiconductor manufacturing facility using all-optical lithography and fully industrial processing. With this approach, we achieve nanoscale gate patterns with excellent yield. In the multi-electron regime, the quantum dots allow good tunnel barrier control—a crucial feature for fault-tolerant two-qubit gates. Single-spin qubit operation using magnetic resonance in the few-electron regime reveals relaxation times of over 1 s at 1 T and coherence times of over 3 ms.

Optimization of preventive maintenance strategies in a multipurpose batch plant: application to semiconductor manufacturing

In this paper, we propose a new and the first MCM system partitioning method considering chip-to-chip delays, chip areas and I/O pins constraints. The proposed method consists of two steps, a clustering step considering the three constraints and an iterative improvement step with mathematical programming. In the first step, we apply two clustering algorithms considering the three constraints and reduce the size of the large MCM system partitioning problem so as to get a solution within a practical computation time. Next, it generates an initial partitioning with 0-1 integer linear programming (ILP) so as to minimize the total wire length. Since there may exist constraint violations in the initial solution, in the second step, we formulate the partitioning problem as a LP problem selecting a maximal independent set and improve it until the total number of cuts is not decreased and the three constraints are satisfied. We also showed that the number of the timing constraints can be reduced by deleting redundant timing constraints. Experimental results showed that the proposed method is able to produce partitions satisfying the three constraints and improves the number of cuts by a 27% on an average and a 30% in maximum over the conventional method [15] considering only two constrains.

In this paper, we link production planning decisions to marketing decisions that involve the price of product groups. The focus of this paper is the development of a closed-loop procedure for aggregate production planning and pricing. We seek to satisfy uncertain demand while minimizing total costs that include material, labour, and inventory holding costs. The procedure is useful for variable demand to update short-term aggregate plans.

At present, it is still impossible to accurately solve realistic problems of production planning and control (PPC) in an acceptable period of time. Therefore numerous heuristic procedures were developed to solve problems of PPC. The efficiency of these procedures is usually appraised by means of statistical analyses. The data necessary for the analyses must meet high requirements to obtain significant and generalizable results from the statistical analyses. A procedure for the generation of test data is presented in the article. The procedure is based on given characteristics. It stochastically produces PPC data of arbitrary complexity. The procedure for the generation of test data is based on a hierarchical concept. The user enters values of aggregated classification numbers which globally characterize the modeled production system and the amount of released production orders. The values of detailed classification numbers are stochastically generated from the aggregated classification numbers. These values form the input for the generation of the PPC data wanted. This generation is stochastically, too. The user may modify both classification numbers and PPC data in order to generate test data equivalent to known practical data or to acquire test data with slightly changing characteristics for analyses of parameter sensitivity.

This paper presents a scheduling heuristic to aid the operators in semiconductor fabrication facilities (commonly referred to as fabs) in choosing what type of lots to process next and whether to change machine setup in order to reduce cycle time. Specifically, this study focused on developing a scheduling heuristic for ion implanters at Cirent Semiconductor (currently Agere Systems) in Orlando, Florida, where implanters are considered to be a bottleneck workstation. The re-entrant flow of production passes several times through the implanters at different stages of the wafer production, requiring changes to the current settings of the workstations and thus incurring a significant setup time. The scheduling heuristic aims at balancing workload levels for implanters processing jobs at different stages of the wafer production lifecycle. This is accomplished by first processing those jobs that contribute most to the increase in inventory levels at the bottleneck workstation. The measures used to evaluate the performance of the proposed heuristic were mean cycle time, mean work in process (WIP), and standard deviation of cycle time. The performance of the proposed heuristic was compared with the scheduling rules currently in use and other commonly used dispatching rules using a validated simulation model. Simulation results showed that the introduced heuristic performs better than all other rules in terms of mean cycle time and WIP in all cases, and better in terms of standard deviation of cycle time for most cases tested. The heuristic can be used at any bottleneck workstation that processes products at different stages of their production cycle and that requires a significant setup time.

Influence of an R&D lot on productivity in semiconductor manufacturing

This paper describes the evolution of the 200 mm generation of automated material handling systems in Intel's semiconductor fabrication facilities. We describe the benefits and challenges in implementing and maintaining these systems. The 300 mm generation of fabrication facilities present some new challenges and opportunities for lowering capital and operational cost while providing for better flexibility through automation. We believe that increased standardization and synergistic design of process equipment, building, operational methodologies and automation systems is required for meeting these new challenges. We conclude by presenting some engineering ideas and design management processes that represent work in progress to meet this objective. We hope to generate discussion and motivate applied research in universities on ideas and equipment that would support cost effective proliferation of automated material handling in the semiconductor industry.

Automated Material Handling Systems (AMHS) have traditionally been used at Intel to store, transport, and load boxes of silicon wafers within semiconductor manufacturing facilities, or "fabs". These systems have been developed to reduce floor space required for storage, reduce damage to wafers from handling, and improve tracking of wafers. More recently, Intel has begun integrating advanced mechanical solutions with intelligent software to optimize factory performance. Now the semiconductor industry is poised to convert from 200mm diameter wafers to 300mm wafers. With this conversion, ergonomic constraints imposed by the new wafer size will drive the industry toward fully automated solutions at a much more rapid pace. Unfortunately, many of the hardware and software products developed for 200mm material handling will not meet the needs of the new 300mm fabs. In this paper, we examine the material handling solutions being developed to meet the unique challenges and opportunities of 300mm semiconductor manufacturing.

ObjectivesThe purpose of this study was to assess potential occupational exposure to chemicals among workers using both qualitative and quantitative information during specific job tasks on the photolithography process of...

The Olympic and Paralympic Games 2012: Literature review of the logistical planning and operational challenges for public health