scholarly journals What Were the Cost Drivers for Publicly Accessible Charging Installations?

2015 ◽  
Author(s):  
Not Given Author
Keyword(s):  
Cost Drivers ◽  
The Cost

Cloud Build Methodology

2021 ◽  
pp. 108-132
Author(s):  
Richard Ehrhardt
Keyword(s):  
Hybrid Cloud ◽  
Design Decisions ◽  
Cost Drivers ◽  
Hybrid Clouds ◽  
Different Types ◽  
The Cost

The cloud build methodology chapter provides an introduction to the build methods for hybrid clouds. It does this by first introducing the concept of a hybrid cloud and the different types of services provides by clouds. It then overviews the components of hybrid clouds and how these components get incorporated into the design. It takes a brief look at the cost drivers with building a cloud to provide background with design decisions to be made. With the background on the design, it takes the reader through the build of a hybrid cloud and how automation can be used to reduce the cost. Lastly, it takes a brief look at a possible direction of cloud builds.

Cost Drivers for 2.5D and 3D Applications

2013 ◽  
Vol 2013 (DPC) ◽  
pp. 000334-000346
Author(s):  
Chet Palesko ◽  
E. Jan Vardaman ◽  
Alan Palesko
Keyword(s):  
High Performance ◽  
Specific Activity ◽  
Cost Effective ◽  
Cost Models ◽  
Network Systems ◽  
Cost Drivers ◽  
Technology Applications ◽  
Silicon Vias ◽  
The Cost ◽  
3D Applications

2.5D and 3D applications using through silicon vias (TSVs) are increasingly being considered as a packaging alternative. Miniaturization and high performance product requirements are driving this move – even though in many cases the cost of both 2.5D and 3D is still high. The primary applications for 2.5D interposers with TSVs are GPUs/CPUs, high-end ASICs, and FPGAs. Adoption for FPGAs has already started. The key to the performance gains in recently introduced FPGAs is the partitioning of an FPGA die into four “slices” that are mounted on a silicon interposer or what Xilinx calls its Stacked Silicon Interconnect technology. Applications for interposers include tablets, gaming, and high-end computing and network systems. The drivers are mainly partitioning large die, integrating single chips into a module, reducing die size where substrate density is the constraint, and using the interposer to minimize the stress on large die that are fabricated with extra-low-k (ELK) dielectrics. The primary applications for 3D solutions are stacked memory cubes and memory plus logic. The true 3D nature of stacking all active silicon allows better miniaturization, but yield issues can quickly drive the cost unacceptably high. This analysis examines the cost drivers for 2.5D and 3D applications. Activity based cost models will be used to analyze the complete cost of fabricating and assembling active die on a silicon interposer and active die stacking on other active die. Total product cost impact - not just the cost of a specific activity - is the focus of this analysis. Since yields play a major role in cost, a sensitivity analysis of the different yields including die yield before wafer probe, die yield after wafer probe, TSV yield, interposer yield, assembly yield, substrate yield, etc. will be presented. The critical yield points in the manufacturing flow and dominant activity cost drivers (equipment, material, and /or labor) will be presented as well as suggested minimum thresholds for 2.5D and 3D technology to be a cost effective technology.

Cost Comparison of 2.5D/3D Packaging to other Packaging Technologies

2013 ◽  
Vol 2013 (1) ◽  
pp. 000429-000433
Author(s):  
Chet Palesko ◽  
Amy Palesko ◽  
E. Jan Vardaman
Keyword(s):  
Cost Reduction ◽  
High Performance ◽  
Cost Comparison ◽  
Through Silicon Vias ◽  
Cost Drivers ◽  
3D Packaging ◽  
Silicon Vias ◽  
The Cost ◽  
3D Applications

2.5D and 3D applications using through silicon vias (TSVs) are increasingly being considered as an alternative to conventional packaging. Miniaturization and high performance product requirements are driving this move, although in many cases the cost of both 2.5D and 3D is still high. In this paper we will identify the major cost drivers for 2.5D and 3D packaging and assess cost reduction progress, including current costs versus expected future costs. We will also compare these costs to alternative packaging.

scholarly journals Study on Key Cost Drivers of Prefabricated Buildings Based on System Dynamics

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Na Lou ◽  
Jingjuan Guo
Keyword(s):  
Cost Control ◽  
Rapid Development ◽  
Construction Cost ◽  
Cost Driver ◽  
Systematic Research ◽  
Cost Drivers ◽  
Building Cost ◽  
Cost Constraints ◽  
The Cost ◽  
Prefabricated Building

The prefabricated building as a major initiative has been put forward by China in recent years to promote the transformation and upgrading of the construction industry, but its rapid development also faces high cost constraints. Therefore, it is necessary and urgent to study the key cost drivers and cost control paths of prefabricated buildings. Most of the current research focuses on the construction cost of prefabricated building as a static object. This article, on the other hand, regards the construction cost of prefabricated building as a dynamic formation process and conducts systematic research from product systems, technical systems, construction processes, and management modes. The influence factors of prefabricated building cost are defined and screened with the help of HSM and previous research results. A cause-and-effect model and cost control model of prefabricated building cost driver are established. Based on the model test of the actual project, the cost generation of prefabricated buildings is simulated. Through sensitivity analysis, key cost drivers of prefabricated building are identified and ranked as degree of design standardization, unit price, prefabrication rate, information technology level, transportation mode, labor level, machinery level, transportation distance, etc. Accordingly, corresponding strategies are proposed for the cost control of prefabricated buildings.

Cell Therapy: Early Process Development and Optimization of the Manufacturing Process are Critical to Ensure Viability of the Product, Quality, Consistency and Cost Efficiency

2015 ◽  
Vol 21 (1) ◽  
Author(s):  
Ohad Karnieli
Keyword(s):  
Cell Therapy ◽  
Cost Efficiency ◽  
Process Development ◽  
Scale Up ◽  
Three Dimensional ◽  
Evolutionary Development ◽  
Cell Therapies ◽  
Cost Drivers ◽  
Living Things ◽  
The Cost

In recent years cell therapies have evolved and matured, moving from academia to industry. Scale up of a process is the natural path of any product evolutionary development and maturation, this process not only allows higher manufacturing capacity to meet demands but rather to increases the yields and reduces cost of goods. Cells are living things that react to the environment and conditions in which they grow, therefore process changes should be done as early as possible. The traditional 2D culturing systems can be truly up scaled, therefore there is a need to advance to bioreactors that will influence the product. Additionally, in order to make cell therapy a viable one, the cost of manufacturing is critical. Cost drivers such as media, serum, footprint, human resource and infrastructure must be optimized without changing the cells critical quality attributes. The paper analyze the main cost drivers on the cost of goods and is based on the experience of cell manufacturing in both traditional 2D and three dimensional (3D) bioreactor systems produced in Pluristem therapeutics GMP site. Furthermore, the paper discussed possible process development steps to insure cost efficiency emphasizing the need and benefit of early process development investment.   

What Are the Cost Drivers for the Major Bowel Bundled Payment Care Improvement Initiative?

2020 ◽  
Vol 64 (1) ◽  
pp. 112-118
Author(s):  
Rocco Ricciardi ◽  
Marilyn A. Moucharite ◽  
Caitlin Stafford ◽  
Guy Orangio ◽  
Patricia L. Roberts
Keyword(s):  
Cost Drivers ◽  
Bundled Payment ◽  
Care Improvement ◽  
The Cost

Effect of Different Cost Drivers on Cost per Anesthesia Minute in Different Anesthesia Subspecialties

2004 ◽  
Vol 101 (6) ◽  
pp. 1435-1443 ◽  
Author(s):  
Martin Schuster ◽  
Thomas Standl ◽  
Joachim A. Wagner ◽  
Jürgen Berger ◽  
Hajo Reißmann ◽  
...  
Keyword(s):  
Multiple Regression Model ◽  
University Hospital ◽  
Cost Drivers ◽  
Personnel Costs ◽  
Facial Surgery ◽  
American Society ◽  
The Cost ◽  
American Society Of Anesthesiologists ◽  
Cost Differences ◽  
Nose And Throat

Background Little is known about differences in costs to provide anesthesia care for different surgical subspecialties and which factors influence the subspecialty-specific costs. Methods In this retrospective study, the authors determined main cost components (preoperative visit, intraoperative personnel costs, material and pharmaceutical costs, and others) for 10,843 consecutive anesthesia cases from a 6-month period in the 10 largest anesthesia subspecialties in their university hospital: ophthalmology; general surgery; obstetrics and gynecology; ear, nose, and throat surgery; oral and facial surgery; neurosurgery; orthopedics; cardiovascular surgery; traumatology; and urology. Using regression analysis, the effect of five presumed cost drivers (anesthesia duration, emergency status, American Society of Anesthesiologists physical status of III or higher, patient age younger 6 yr, and placement of invasive monitoring) on subspecialty-specific costs per anesthesia minute were analyzed. Results Both personnel costs for anesthesiologists and total costs calculated per anesthesia minute were inversely correlated with the duration of anesthesia (adjusted R2 = 0.75 and 0.69, respectively), i.e., they were higher for subspecialties with short cases and lower for subspecialties with longer cases. The multiple regression model showed that differences in anesthesia duration alone accounted for the majority of the cost differences, whereas the other presumed cost drivers added only little to explain subspecialty-specific cost differences. Conclusions Different anesthesia subspecialties show significant and financially important differences regarding their specific costs. Personnel costs and total costs are highest for subspecialties with the shortest cases. Other analyzed cost drivers had little effect on subspecialty-specific costs. In the light of these cost differences, a detailed cost analysis seems necessary before the profitability of an anesthesia subspecialty can be assessed.

scholarly journals Cost Estimate Model for Software Projects using GREYWOLF Algorithm and COCOMO Model

2019 ◽  
Vol 8 (4) ◽  
pp. 7824-7828
Keyword(s):  
Cost Estimation ◽  
Project Manager ◽  
Cost Estimate ◽  
Software System ◽  
Actual Cost ◽  
Software Projects ◽  
Cost Drivers ◽  
Cocomo Model ◽  
The Cost ◽  
System Project

Cost estimation analysis for the software system project is the foremost difficult tasks in software organizations. In this paper, a comparison between an estimate and actual effort was done by applying the grey wolf’s algorithm to predict the effort and time of this software system for a given archive. The intermediate semi-detached COCOMO model was used with the grey wolf’s algorithm by taking the KLOC of the dataset as input, additionally to fifteen cost drivers and giving effort and time as output. The recommended model of the cost estimation helps the project manager by offering a fast and truly estimates the hassle and time of software system project which is nearer to the actual cost.

scholarly journals A PROPOSED CASE STUDY FIELD RESEARCH METHODOLOGY TO TEST COST DRIVERS: AN EXAMPLE OF PROPOSED FIELD STUDY AT A NUCLEAR MEDICINE UNIT

2021 ◽  
pp. 123-129
Keyword(s):  
Nuclear Medicine ◽  
Research Methodology ◽  
Value Added ◽  
Field Research ◽  
Cost Driver ◽  
Cost Drivers ◽  
Managerial Decisions ◽  
Industry Research ◽  
The Cost

This paper illustrates how to use case study method to conduct the cost driver research at hospitals by identifying activity-based cost drivers at the nuclear medicine unit (NMU) of a teaching hospital. I argue that recognizing the activity-based cost could improve the accuracy of estimating costs by identifying the underutilized resources and value-added and non-value-added cost drivers, to reduce non-value-added costs; thereby, facilitating the management to make better informed managerial decisions (e.g., improving pricing practices and using resources more efficiently). Therefore, I believe that this study may provide a useful inference to hospitals to improve the quality and quantity of the service, which they (or would) provide. Furthermore, this paper possibly provides an informative research methodology for researchers by showing how to extend the current literature by applying the same cost analysis research model on a different dataset for the health care industry research.

scholarly journals The Use of Experts Panels in ERP Cost Estimation Research

2013 ◽  
pp. 675-688
Author(s):  
Ahmed Elragal ◽  
Moutaz Haddara
Keyword(s):  
Enterprise Resource Planning ◽  
Cost Estimation ◽  
Resource Planning ◽  
Exploratory Research ◽  
Estimation Model ◽  
Cost Drivers ◽  
Cost Estimation Model ◽  
Visualization Techniques ◽  
The Cost ◽  
Cost Factors

This chapter is an effort towards illustrating the use of expert panels (EP) as a means of eliciting knowledge from a group of enterprise resource planning (ERP) experts in an exploratory research. The development of a cost estimation model for ERP adoptions is very crucial for research and practice, and that was the main reason behind the willingness of experts to participate in this research. The use of EP was very beneficial as it involved various data collection and visualization techniques, as well as data validation and confirmation. Arguments for using EP over other group techniques are presented in this chapter. Experts modified and enhanced the initial cost drivers list and their sub-factors significantly, as they added, modified, merged and split different costs. Moreover, they ranked the cost drivers according to their weight on total costs. All of this helped the authors to better understand relationships among various cost factors.

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