Matching Items (4)

134875-Thumbnail Image.png

An Analysis of Craft Labor Productivity

Description

Productivity in the construction industry is an essential measure of production efficiency and economic progress, quantified by craft laborers' time spent directly adding value to a project. In order to

Productivity in the construction industry is an essential measure of production efficiency and economic progress, quantified by craft laborers' time spent directly adding value to a project. In order to better understand craft labor productivity as an aspect of lean construction, an activity analysis was conducted at the Arizona State University Palo Verde Main engineering dormitory construction site in December of 2016. The objective of this analysis on craft labor productivity in construction projects was to gather data regarding the efficiency of craft labor workers, make conclusions about the effects of time of day and other site-specific factors on labor productivity, as well as suggest improvements to implement in the construction process. Analysis suggests that supporting tasks, such as traveling or materials handling, constitute the majority of craft labors' efforts on the job site with the highest percentages occurring at the beginning and end of the work day. Direct work and delays were approximately equal at about 20% each hour with the highest peak occurring at lunchtime between 10:00 am and 11:00 am. The top suggestion to improve construction productivity would be to perform an extensive site utilization analysis due to the confined nature of this job site. Despite the limitations of an activity analysis to provide a complete prospective of all the factors that can affect craft labor productivity as well as the small number of days of data acquisition, this analysis provides a basic overview of the productivity at the Palo Verde Main construction site. Through this research, construction managers can more effectively generate site plans and schedules to increase labor productivity.

Contributors

Created

Date Created
  • 2016-12

135058-Thumbnail Image.png

A Prediction-Based Study Of Lean Methodologies In Hospital Emergency Departments

Description

This study analyzes the various applications of Lean Methodologies in emergency departments (ED) from the years 2005 through 2010. These data were then used to create a predictive model that

This study analyzes the various applications of Lean Methodologies in emergency departments (ED) from the years 2005 through 2010. These data were then used to create a predictive model that hospitals can use to assess the benefits of using lean within their ED. Metrics studied include 1) rate of patients that left the ED without being seen 2) length of stay and 3) overall patient satisfaction. These metrics were extracted from published studies and used to create a linear regression model, which could be applied to an ED to predict its status after implementing a lean project. After developing these formulas, they were applied to the ED of fictional hospital T-1 in order to predict benefit. After determining the approximate values for the post-lean metrics, an estimate of the financial benefit was developed in conjunction with a financial executive at Chandler Regional Medical Center, in Chandler, Arizona.

Contributors

Agent

Created

Date Created
  • 2016-12

136909-Thumbnail Image.png

Engineering Lean, Packaged Energy Systems for Rapid, Economical Deployment and Distributed Generation

Description

The following document addresses two grand challenges posed to engineers: to make solar energy economically viable and to restore and improve urban infrastructure. Design solutions to these problems consist of

The following document addresses two grand challenges posed to engineers: to make solar energy economically viable and to restore and improve urban infrastructure. Design solutions to these problems consist of the preliminary designs of two energy systems: a Packaged Photovoltaic (PPV) energy system and a natural gas based Modular Micro Combined Cycle (MMCC) with 3D renderings. Defining requirements and problem-solving approach methodology for generating complex design solutions required iterative design and a thorough understanding of industry practices and market trends. This paper briefly discusses design specifics; however, the major emphasis is on aspects pertaining to economical manufacture, deployment, and subsequent suitability to address the aforementioned challenges. The selection of these systems is based on the steady reduction of PV installation costs in recent years (average among utility, commercial, and residential down 27% from Q4 2012 to Q4 2013) and the dramatic decline in natural gas prices to $5.61 per thousand cubic feet. In addition, a large number of utility scale coal-based power plants will be retired in 2014, many due to progressive emission criteria, creating a demand for additional power systems to offset the capacity loss and to increase generating capacity in order to facilitate the ever-expanding world population. The proposed energy systems are not designed to provide power to the masses through a central location. Rather, they are intended to provide economical, reliable, and high quality power to remote locations and decentralized power to community-based grids. These energy systems are designed as a means of transforming and supporting the current infrastructure through distributed electricity generation.

Contributors

Agent

Created

Date Created
  • 2014-05

150322-Thumbnail Image.png

Energy and carbon dioxide impacts from lean logistics and retailing systems: a discrete-event simulation approach for the consumer goods industry

Description

Consumer goods supply chains have gradually incorporated lean manufacturing principles to identify and reduce non-value-added activities. Companies implementing lean practices have experienced improvements in cost, quality, and demand responsiveness. However

Consumer goods supply chains have gradually incorporated lean manufacturing principles to identify and reduce non-value-added activities. Companies implementing lean practices have experienced improvements in cost, quality, and demand responsiveness. However certain elements of these practices, especially those related to transportation and distribution may have detrimental impact on the environment. This study asks: What impact do current best practices in lean logistics and retailing have on environmental performance? The research hypothesis of this dissertation establishes that lean distribution of durable and consumable goods can result in an increased amount of carbon dioxide emissions, leading to climate change and natural resource depletion impacts, while lean retailing operations can reduce carbon emissions. Distribution and retailing phases of the life cycle are characterized in a two-echelon supply chain discrete-event simulation modeled after current operations from leading organizations based in the U.S. Southwest. By conducting an overview of critical sustainability issues and their relationship with consumer products, it is possible to address the environmental implications of lean logistics and retailing operations. Provided the waste reduction nature from lean manufacturing, four lean best practices are examined in detail in order to formulate specific research propositions. These propositions are integrated into an experimental design linking annual carbon dioxide equivalent emissions to: (1) shipment frequency between supply chain partners, (2) proximity between decoupling point of products and final customers, (3) inventory turns at the warehousing level, and (4) degree of supplier integration. All propositions are tested through the use of the simulation model. Results confirmed the four research propositions. Furthermore, they suggest synergy between product shipment frequency among supply chain partners and product management due to lean retailing practices. In addition, the study confirms prior research speculations about the potential carbon intensity from transportation operations subject to lean principles.

Contributors

Agent

Created

Date Created
  • 2011