The Experts below are selected from a list of 1209 Experts worldwide ranked by ideXlab platform
Anthony L Patti - One of the best experts on this subject based on the ideXlab platform.
-
the shape of protective capacity in unbalanced production systems with unplanned Machine Downtime
Production Planning & Control, 2008Co-Authors: Anthony L Patti, Kevin Watson, John H BlackstoneAbstract:Several studies have shown that when both statistical fluctuations and dependent events exist, unbalanced production lines out-perform balanced lines. By definition, unbalanced lines have some amount of protective capacity built into them; however, little research exists to address the question of quantity and position of protective capacity necessary to counteract the impact of variation on system performance. This research seeks to improve our understanding concerning the shape of protective capacity in unbalanced lines when faced with variation in the form of unplanned Machine Downtime. Both Kanban and drum-buffer-rope (DBR) controlled lines are investigated. Results show that balancing the protective capacity yields superior results over both increasing and decreasing protective capacity shapes (holding average protective capacity equal). Results also show that Kanban lines behave differently than DBR lines.
-
a comparison of jit and toc buffering philosophies on system performance with unplanned Machine Downtime
International Journal of Production Research, 2008Co-Authors: K J Watson, Anthony L PattiAbstract:The impact of buffering under just in time (JIT) and theory of constraints (TOC) is studied to determine whether a difference in performance exists in systems faced with unplanned Machine Downtime. Comparisons are based on results obtained from simulation of a five-station cell utilised in computer substrate manufacturing. Analysis of the simulation output suggests that the TOC technique, drum–buffer–rope (DBR), achieves higher levels of performance as measured by total output and lead time while reducing inventory requirements relative to the tested JIT technique, Kanban. Improved system performance stems from the strategic placement of buffers in DBR, which maximises protection of the constraint from variation rather than attempting to protect each individual station. Further, analysis suggests that DBR systems are more robust than JIT systems in that they are able to maintain higher levels of system performance across a range of inventory levels.
S Stathakis - One of the best experts on this subject based on the ideXlab platform.
-
su e t 173 clinical comparison of treatment plans and fallback plans for Machine Downtime
Medical Physics, 2015Co-Authors: W Cruz, P Papanikolaou, P Mavroidis, S StathakisAbstract:Purpose: The purpose of this study was to determine the clinical effectiveness and dosimetric quality of fallback planning in relation to Machine Downtime. Methods: Plans for a Varian Novalis TX were mimicked, and fallback plans using an Elekta VersaHD Machine were generated using a dual arc template. Plans for thirty (n=30) patients of various treatment sites optimized and calculated using RayStation treatment planning system. For each plan, a fall back plan was created and compared to the original plan. A dosimetric evaluation was conducted using the homogeneity index, conformity index, as well as DVH analysis to determine the quality of the fallback plan on a different treatment Machine. Fallback plans were optimized for 60 iterations using the imported dose constraints from the original plan DVH to give fallback plans enough opportunity to achieve the dose objectives. Results: The average conformity index and homogeneity index for the NovalisTX plans were 0.76 and 10.3, respectively, while fallback plan values were 0.73 and 11.4. (Homogeneity =1 and conformity=0 for ideal plan) The values to various organs at risk were lower in the fallback plans as compared to the imported plans across most organs at risk. Isodose difference comparisons between plans were also compared and the average dose difference across all plans was 0.12%. Conclusion: The clinical impact of fallback planning is an important aspect to effective treatment of patients. With the complexity of LINACS increasing every year, an option to continue treating during Machine Downtime remains an essential tool in streamlined treatment execution. Fallback planning allows the clinic to continue to run efficiently should a treatment Machine become offline due to maintenance or repair without degrading the quality of the plan all while reducing strain on members of the radiation oncology team.
W Cruz - One of the best experts on this subject based on the ideXlab platform.
-
su e t 173 clinical comparison of treatment plans and fallback plans for Machine Downtime
Medical Physics, 2015Co-Authors: W Cruz, P Papanikolaou, P Mavroidis, S StathakisAbstract:Purpose: The purpose of this study was to determine the clinical effectiveness and dosimetric quality of fallback planning in relation to Machine Downtime. Methods: Plans for a Varian Novalis TX were mimicked, and fallback plans using an Elekta VersaHD Machine were generated using a dual arc template. Plans for thirty (n=30) patients of various treatment sites optimized and calculated using RayStation treatment planning system. For each plan, a fall back plan was created and compared to the original plan. A dosimetric evaluation was conducted using the homogeneity index, conformity index, as well as DVH analysis to determine the quality of the fallback plan on a different treatment Machine. Fallback plans were optimized for 60 iterations using the imported dose constraints from the original plan DVH to give fallback plans enough opportunity to achieve the dose objectives. Results: The average conformity index and homogeneity index for the NovalisTX plans were 0.76 and 10.3, respectively, while fallback plan values were 0.73 and 11.4. (Homogeneity =1 and conformity=0 for ideal plan) The values to various organs at risk were lower in the fallback plans as compared to the imported plans across most organs at risk. Isodose difference comparisons between plans were also compared and the average dose difference across all plans was 0.12%. Conclusion: The clinical impact of fallback planning is an important aspect to effective treatment of patients. With the complexity of LINACS increasing every year, an option to continue treating during Machine Downtime remains an essential tool in streamlined treatment execution. Fallback planning allows the clinic to continue to run efficiently should a treatment Machine become offline due to maintenance or repair without degrading the quality of the plan all while reducing strain on members of the radiation oncology team.
S.m. Meerkov - One of the best experts on this subject based on the ideXlab platform.
-
Statics and Dynamics of Re-Entrant Production Lines
IFAC Proceedings Volumes, 2020Co-Authors: Michael Hassoun, S.m. MeerkovAbstract:Abstract A model of a re-entrant line, consisting of the bottleneck workcenter and time delays representing other workcenters, is considered. Its mathematical description is provided and performance metrics are introduced. The steady states of this model and their stability properties are investigated under two dispatch policies – First Buffer First Served (FBFS) and Last Buffer First Served (LBFS) – and under constant release rate. The transients due to Machine Downtime are also analyzed. It is shown that, although LBFS may be viewed as having superior steady state characteristics, it induces longer and more volatile transients than FBFS and, in some cases, periodic and chaotic regimes.
-
Equilibria, Stability, and Transients in Re-Entrant Lines Under FBFS and LBFS Dispatch and Constant Release
IEEE Transactions on Semiconductor Manufacturing, 2012Co-Authors: Michael Hassoun, S.m. MeerkovAbstract:A model of a re-entrant line, consisting of the bottleneck workcenter and time delays representing other workcenters, is considered. Its mathematical description is provided and performance metrics are introduced. The steady states of this model and their stability properties are investigated under two dispatch policies-first buffer first served (FBFS) and last buffer first served (LBFS)-and under constant release rate. The transients due to Machine Downtime are also analyzed. It is shown that, although LBFS may be viewed as having superior steady-state characteristics, it induces longer and more volatile transients than FBFS and, in some cases, periodic and chaotic regimes.
-
buffer capacity for accommodating Machine Downtime in serial production lines
International Journal of Production Research, 2002Co-Authors: E. Enginarlar, S.m. Meerkov, Jingshan Li, Rachel Q ZhangAbstract:This paper investigates the smallest level of buffering (LB), necessary to ensure the desired production rate in serial lines with unreliable Machines. The reliability of Machines is assumed to obey either exponential, or Erlang, or Rayleigh models. The LB is measured in units of the average Downtime, T down . The dependence of LB on the reliability model, the number of Machines, M , the average uptime, T up , and the efficiency, e = T up /( T up + T down ) is analysed. It is shown that reliability models with larger coefficient of variation require larger LB, and an empirical law that connects LB of the exponential model with those for other reliability models is established. It is shown that LB is an increasing function of M , but with an exponentially decreasing rate, saturating at around M = 10. Also, it is shown that LB does not depend explicitly on T up and is a decreasing function of e . Based on these results, rules-of-thumb are provided for selecting buffer capacity, which guarantee sufficiently ...
-
Buffer capacity for accommodating Machine Downtime in serial production lines
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001Co-Authors: E. Enginarlar, Jiangshan Li, S.m. MeerkovAbstract:This paper provides a method for calculating the smallest level of buffering (LB), necessary to ensure the desired production rate in serial lines with unreliable Machines.
K J Watson - One of the best experts on this subject based on the ideXlab platform.
-
a comparison of jit and toc buffering philosophies on system performance with unplanned Machine Downtime
International Journal of Production Research, 2008Co-Authors: K J Watson, Anthony L PattiAbstract:The impact of buffering under just in time (JIT) and theory of constraints (TOC) is studied to determine whether a difference in performance exists in systems faced with unplanned Machine Downtime. Comparisons are based on results obtained from simulation of a five-station cell utilised in computer substrate manufacturing. Analysis of the simulation output suggests that the TOC technique, drum–buffer–rope (DBR), achieves higher levels of performance as measured by total output and lead time while reducing inventory requirements relative to the tested JIT technique, Kanban. Improved system performance stems from the strategic placement of buffers in DBR, which maximises protection of the constraint from variation rather than attempting to protect each individual station. Further, analysis suggests that DBR systems are more robust than JIT systems in that they are able to maintain higher levels of system performance across a range of inventory levels.
