Stochastic Energy Opportunity Windows in Advanced Manufacturing Systems

2015 ◽  
Author(s):  
Yang Li ◽  
Qing Chang ◽  
Xiaoning Jin ◽  
Jun Ni
Keyword(s):  
Energy Saving ◽  
Manufacturing Systems ◽  
Production Control ◽  
Environmental Concern ◽  
Markov Chain Model ◽  
Cost Effective ◽  
Chain Model ◽  
Global Competitiveness ◽  
Improve Energy Efficiency ◽  
Multistage Manufacturing

To improve energy efficiency is becoming more and more critical for manufacturing enterprises because of the rising energy costs, increased global competitiveness, environmental concern and more government regulations. Production control has been considered as one of the most cost-effective methods to achieve the goal. This paper discusses the energy saving opportunities in a multistage manufacturing system through strategically shut down machines to reduce their running time. We start from the investigation on what is the longest time that machines can be shut down or turn to energy saving mode without affecting system production. Then, energy opportunity windows (EOWs) of machines are defined. A Markov chain model is developed to estimate the EOWs. A case study is conducted to demonstrate the proposed model and its potential on energy saving in multistage manufacturing systems.

Event-Based Production Control for Energy Efficiency Improvement in Sustainable Multistage Manufacturing Systems

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Yang Li ◽  
Jun-Qiang Wang ◽  
Qing Chang
Keyword(s):  
Energy Efficiency ◽  
Energy Saving ◽  
Energy Cost ◽  
Manufacturing Systems ◽  
Production Control ◽  
Control Method ◽  
Sustainable Manufacturing ◽  
Environmental Crisis ◽  
System Level ◽  
Event Based

There has been an increasing trend for manufacturers to shift toward sustainable manufacturing strategies in response to an ever-growing pressure from fluctuating energy price and environmental crisis. Reducing energy consumption is considered as an important step to achieve the sustainability of a production system. This paper proposes an event-based control methodology to improve the production energy efficiency through strategically switching appropriate stations to energy saving mode. Based on an event-based analysis of production dynamics, an analytical approach is developed to quantitatively predict the system level production loss resulted from an energy saving control event (ESCE). A genetic-based control algorithm is proposed to balance the trade-off between the gain from energy saving and the expense of throughput loss. The energy improvement analysis results in a fundamental understanding of production energy dynamics and a significant decrease of energy cost for a manufacturing facility. Numerical case studies are performed to validate the effectiveness of the proposed method. It is found that the control method can effectively reduce energy cost, while only slightly impacting production.

scholarly journals Motion – Laparoscopic Nissen Fundoplication Is More Cost-Effective than Oral PPI Administration: Arguments against the Motion

2002 ◽  
Vol 16 (9) ◽  
pp. 627-631 ◽  
Author(s):  
Amnon Sonnenberg
Keyword(s):  
Cost Effectiveness ◽  
Nissen Fundoplication ◽  
Markov Chain Model ◽  
Treatment Options ◽  
Cost Effective ◽  
Chain Model ◽  
Acid Suppression Therapy ◽  
Laparoscopic Nissen ◽  
Logical Fallacies ◽  
Surgical Treatments

Discussion of the cost effectiveness of medical and surgical treatments of gastroesophageal reflux disease (GERD) is plagued by a number of logical fallacies. Several of these defects in reasoning are reviewed. For example, it is inappropriate to compare the costs of therapies unless they are equally effective. The relative cost effectiveness of various treatment options is difficult to determine because monetary expenditures and gains in health status cannot easily be measured in commensurate units. Not everything can be translated into incremental cost effectiveness ratios. Two decision analyses from European investigators seemed to show that Nissen fundoplication was more cost effective than long term acid-suppression therapy, but they failed to consider the costs of surgical complications and failures. The most comprehensive decision analysis, employing a Markov chain model, found that the two treatment options were roughly equivalent, at least during the first seven years of follow-up. Decision analyses often do not reflect actual practice patterns and cannot provide solutions to problems that cannot be solved by appropriate medical reasoning. Moreover, results that are reported by specialized surgical centres probably cannot be duplicated by less experienced surgeons. The increasing incidence of esophageal adenocarcinoma has been erroneously attributed to the use of potent acid-suppressant medications, but the actual cause has been shown to be the decreased prevalence ofHelicobacter pylori. There are no significant differences in the incidence of this tumour after medical or surgical therapy of GERD. It is unlikely, however, that arguments will convince proponents of one treatment or another to change their opinions.

Stochastic Maintenance Opportunity Windows for Serial Production Line

2015 ◽  
Author(s):  
Jing Zou ◽  
Qing Chang ◽  
Yong Lei ◽  
Guoxian Xiao ◽  
Jorge Arinez
Keyword(s):  
Stochastic Model ◽  
Energy Saving ◽  
Manufacturing Systems ◽  
Production Control ◽  
Production Systems ◽  
Critical Element ◽  
Serial Production ◽  
Manufacturing Plants ◽  
Future Prediction ◽  
Saving Mode

Timely performance of preventive maintenance (PM) tasks is a critical element of manufacturing systems. The current PM at most manufacturing plants is to conduct maintenance tasks during non-production shifts, breaks, or other scheduled downtime. This practice may introduce unnecessary extra labor and overhead costs. Therefore, there is need to look for hidden maintenance opportunities to perform PM tasks during normal production time without impacting throughput. Additional benefit of the hidden opportunity window is that it can be translated to hidden energy saving opportunity during which machines can be strategically shut down or turned to energy saving mode while PM can be performed. Since production schedules are always made beforehand, the development of opportunity window and the downtime schedule need future prediction about the production system. In this paper, a stochastic model of the downtime opportunity on serial production systems is developed. Based on the stochastic model, revised opportunity window and recovery time is defined, which can help on production control on deciding when and where to insert the downtime events and the duration of the downtime events for the incoming process.

Type II Sleep Mode Operation for IEEE 802.16e Based WiMAX

2011 ◽  
Vol 128-129 ◽  
pp. 343-349
Author(s):  
Jian Bin Xue ◽  
Song Bai Li ◽  
Ting Zhang ◽  
Wen Hua Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Saving ◽  
Markov Chain Model ◽  
Broad Band ◽  
Traffic Load ◽  
Sleep Mode ◽  
Chain Model ◽  
Ieee 802.16E ◽  
Mode Operation ◽  
Set Up

To overcome the flaw of energy efficiency drop in broad band wireless communication with the short time sleep, the energy-saving mechanism of the sleep mode operation was researched in IEEE 802.16e. In this paper we propose a dynamic algorithm to tune the ratio of the sleep windows and receive windows according to the traffic load. Then, a Markov chain model was set up to analyze the energy efficiency and mean access delay. NS2 simulation results show that the proposed algorithm can achieve marked gain in energy efficiency compared to the traditional energy saving mechanism.

An Efficient Markov Chain Model for the Simulation of Heterogeneous Soil Structure

2004 ◽  
Vol 68 (2) ◽  
pp. 346 ◽  
Author(s):  
Keijan Wu ◽  
Naoise Nunan ◽  
John W. Crawford ◽  
Iain M. Young ◽  
Karl Ritz
Keyword(s):  
Markov Chain ◽  
Soil Structure ◽  
Markov Chain Model ◽  
Chain Model ◽  
Heterogeneous Soil

Data Mining Technique Applied To DNA Sequencing

2015 ◽  
Vol 2 (7) ◽  
pp. 18
Author(s):  
R. Jamuna
Keyword(s):  
Data Mining ◽  
Dna Methylation ◽  
Markov Chain ◽  
Human Genome ◽  
Transition Probabilities ◽  
Markov Chain Model ◽  
Effective Means ◽  
Cpg Islands ◽  
Chain Model ◽  
The Given

CpG islands (CGIs) play a vital role in genome analysis as genomic markers.  Identification of the CpG pair has contributed not only to the prediction of promoters but also to the understanding of the epigenetic causes of cancer. In the human genome [1] wherever the dinucleotides CG occurs the C nucleotide (cytosine) undergoes chemical modifications. There is a relatively high probability of this modification that mutates C into a T. For biologically important reasons the mutation modification process is suppressed in short stretches of the genome, such as ‘start’ regions. In these regions [2] predominant CpG dinucleotides are found than elsewhere. Such regions are called CpG islands. DNA methylation is an effective means by which gene expression is silenced. In normal cells, DNA methylation functions to prevent the expression of imprinted and inactive X chromosome genes. In cancerous cells, DNA methylation inactivates tumor-suppressor genes, as well as DNA repair genes, can disrupt cell-cycle regulation. The most current methods for identifying CGIs suffered from various limitations and involved a lot of human interventions. This paper gives an easy searching technique with data mining of Markov Chain in genes. Markov chain model has been applied to study the probability of occurrence of C-G pair in the given   gene sequence. Maximum Likelihood estimators for the transition probabilities for each model and analgously for the  model has been developed and log odds ratio that is calculated estimates the presence or absence of CpG is lands in the given gene which brings in many  facts for the cancer detection in human genome.

scholarly journals Performance Analysis of Synchronous Multi-Radio Multi-Link MAC Protocols in IEEE 802.11be Extremely High Throughput WLANs

2020 ◽  
Vol 11 (1) ◽  
pp. 317
Author(s):  
Taewon Song ◽  
Taeyoon Kim
Keyword(s):  
Ieee 802.11 ◽  
Markov Chain Model ◽  
Careful Consideration ◽  
Mac Protocols ◽  
Media Access Control ◽  
Chain Model ◽  
Distributed Coordination ◽  
Media Access ◽  
Medium Access ◽  
Coordination Function

The representative media access control (MAC) mechanism of IEEE 802.11 is a distributed coordination function (DCF), which operates based on carrier-sense multiple access with collision avoidance (CSMA/CA) with binary exponential backoff. The next amendment of IEEE 802.11 being developed for future Wi-Fi by the task group-be is called IEEE 802.11be, where the multi-link operation is mainly discussed when it comes to MAC layer operation. The multi-link operation discussed in IEEE 802.11be allows multi-link devices to establish multiple links and operate them simultaneously. Since the medium access on a link may affect the other links, and the conventional MAC mechanism has just taken account of a single link, the DCF should be used after careful consideration for multi-link operation. In this paper, we summarize the DCFs being reviewed to support the multi-radio multi-link operation in IEEE 802.11be and analyze their performance using the Markov chain model. Throughout the extensive performance evaluation, we summarize each MAC protocol’s pros and cons and discuss essential findings of the candidate MAC protocols.

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