scholarly journals Simulating the benefit of disruption prevention in assembly

2019 ◽  
Vol 14 (1) ◽  
pp. 214-231 ◽  
Author(s):  
Peter Burggraef ◽  
Johannes Wagner ◽  
Matthias Dannapfel ◽  
Sebastian Patrick Vierschilling
Keyword(s):  
Influence Factors ◽  
Simulation Models ◽  
Disruption Management ◽  
Assembly Systems ◽  
Daily Production ◽  
Content Type ◽  
Delivery Times ◽  
Management Measures ◽  
Beneficial Impact ◽  
Group Assembly

Purpose The purpose of this paper is to investigate the benefit of pre-emptive disruption management measures for assembly systems towards the target dimension adherence to delivery times. Design/methodology/approach The research was conducted by creating simulation models for typical assembly systems and measuring its varying throughput times due to changes in their disruption profiles. Due to the variability of assembly systems, key influence factors were investigated and used as a foundation for the simulation setup. Additionally, a disruption profile for each simulated process was developed, using the established disruption categories material, information and capacity. The categories are described by statistical distributions, defining the interval between the disruptions and the disruption duration. By a statistical experiment plan, the effect of a reduced disruption potential onto the throughput time was investigated. Findings Pre-emptive disruption management is beneficial, but its benefit depends on the operated assembly system and its organisation form, such as line or group assembly. Measures have on average a higher beneficial impact on group assemblies than on line assemblies. Furthermore, it was proven that the benefit, in form of better adherence to delivery times, per reduced disruption potential has a declining character and approximates a distinct maximum. Originality/value Characterising the benefit of pre-emptive disruption management measures enables managers to use this concept in their daily production to minimise overall costs. Despite the hardly predictable influence of pre-emptive disruption measures, these research results can be implemented into a heuristic for efficiently choosing these measures.

Modeling of assembly systems with complex structures for throughput analysis during transients

2019 ◽  
Vol 39 (2) ◽  
pp. 262-271
Author(s):  
Yukan Hou ◽  
Yuan Li ◽  
Yuntian Ge ◽  
Jie Zhang ◽  
Shoushan Jiang
Keyword(s):  
Steady State ◽  
Fixed Point Theory ◽  
Point Theory ◽  
Assembly Systems ◽  
Complex Structures ◽  
Throughput Performance ◽  
Throughput Analysis ◽  
Content Type ◽  
Serial Production Lines ◽  
Transient And Steady State

Purpose The purpose of this paper is to present an analytical method for throughput analysis of assembly systems with complex structures during transients. Design/methodology/approach Among the existing studies on the performance evaluation of assembly systems, most focus on the system performance in steady state. Inspired by the transient analysis of serial production lines, the state transition matrix is derived considering the characteristics of merging structure in assembly systems. The system behavior during transients is described by an ergodic Markov chain, with the states being the occupancy of all buffers. The dynamic model for the throughput analysis is solved using the fixed-point theory. Findings This method can be used to predict and evaluate the throughput performance of assembly systems in both transient and steady state. By comparing the model calculation results with the simulation results, this method is proved to be accurate. Originality/value This proposed modeling method can depict the throughput performance of assembly systems in both transient and steady state, whereas most exiting methods can be used for only steady-state analysis. In addition, this method shows the potential for the analysis of complex structured assembly systems owing to the low computational complexity.

scholarly journals Assessing asset monitoring levels for maintenance operations

2015 ◽  
Vol 26 (5) ◽  
pp. 632-659 ◽  
Author(s):  
Abdullah A Alabdulkarim ◽  
Peter Ball ◽  
Ashutosh Tiwari
Keyword(s):  
Asset Management ◽  
Business Models ◽  
Discrete Event ◽  
Dynamic Modelling ◽  
Simulation Models ◽  
Content Type ◽  
Event Simulation ◽  
Product Service ◽  
Asset Monitoring ◽  
The Impact

Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

Adaptive response prediction for aerodynamic shape optimization

2017 ◽  
Vol 34 (5) ◽  
pp. 1485-1500
Author(s):  
Leifur Leifsson ◽  
Slawomir Koziel
Keyword(s):  
Shape Optimization ◽  
Adaptive Response ◽  
Simulation Models ◽  
Response Prediction ◽  
High Fidelity ◽  
High Fidelity Simulation ◽  
Aerodynamic Shape Optimization ◽  
Content Type ◽  
Aerodynamic Shape ◽  
Fidelity Model

Purpose The purpose of this paper is to reduce the overall computational time of aerodynamic shape optimization that involves accurate high-fidelity simulation models. Design/methodology/approach The proposed approach is based on the surrogate-based optimization paradigm. In particular, multi-fidelity surrogate models are used in the optimization process in place of the computationally expensive high-fidelity model. The multi-fidelity surrogate is constructed using physics-based low-fidelity models and a proper correction. This work introduces a novel correction methodology – referred to as the adaptive response prediction (ARP). The ARP technique corrects the low-fidelity model response, represented by the airfoil pressure distribution, through suitable horizontal and vertical adjustments. Findings Numerical investigations show the feasibility of solving real-world problems involving optimization of transonic airfoil shapes and accurate computational fluid dynamics simulation models of such surfaces. The results show that the proposed approach outperforms traditional surrogate-based approaches. Originality/value The proposed aerodynamic design optimization algorithm is novel and holistic. In particular, the ARP correction technique is original. The algorithm is useful for fast design of aerodynamic surfaces using high-fidelity simulation data in moderately sized search spaces, which is challenging using conventional methods because of excessive computational costs.

Who is more likely to become business angels?

2014 ◽  
Vol 6 (1) ◽  
pp. 4-20 ◽  
Author(s):  
Yaokuang Li ◽  
Li Ling ◽  
Juan Wu ◽  
Peng Li
Keyword(s):  
Influence Factors ◽  
Positive Influence ◽  
Clear Understanding ◽  
Logit Analysis ◽  
Business Angels ◽  
Investment Activity ◽  
Content Type ◽  
Angel Investment ◽  
Investment In China ◽  
Practical Implications

Purpose – The paper is aimed to obtain a clear understanding of influence factors that can increase the possibility to be business angels (BA). Design/methodology/approach – This study develops the 3A model in the Chinese context to design questionnaire, and 334 questionnaires are obtained via focus group sample and targeted snowball approach, and the multinomial logit analysis is used to test a serious of hypotheses. Findings – The paper confirmed that the entrepreneurial experience and wealth are determinants of investment for potential BA, and the wealth have both directly and indirectly positive influence on investment activity through risk preference, namely that richer people prefer risk which impel them to invest as BA. Research limitations/implications – There are two limitations in the paper: first, the macro environment in China has not been taken into consideration in the model; second, the source of the sample focuses on the developed cities in the middle and eastern of China, only reflect the characteristic of angels in these areas, which may somewhat diverges from the reality. Practical implications – The paper would contribute to form the policy which could promote the development of angel investment in China. Originality/value – This paper conducts a preliminary exploration of the factors that have impact on Chinese BA' investment activity based on current research.

Novel fractional hybrid impedance control of series elastic muscle-tendon actuator

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Javad Fotuhi ◽  
Zafer Bingul
Keyword(s):  
Contact Stress ◽  
Impedance Control ◽  
Robustness Analysis ◽  
Simulation Models ◽  
Experimental Results ◽  
Uncertain Environments ◽  
Content Type ◽  
Force Tracking ◽  
Comparative Results ◽  
Series Elastic

Purpose This paper aims to develope a novel fractional hybrid impedance control (FHIC) approach for high-sensitive contact stress force tracking control of the series elastic muscle-tendon actuator (SEM-TA) in uncertain environments. Design/methodology/approach In three different cases, the fractional parameters of the FHIC were optimized with the particle swarm optimization algorithm. Its adaptability to the pressure of the sole of the foot on real environments such as grass (soft), carpet (medium) and solid floors (hard) is far superior to traditional impedance control. The main aim of this paper is to derive the dynamic simulation models of the SEM-TA, to develop a control architecture allowing for high-sensitive contact stress force control in three cases and to verify the simulation models and the proposed controller with experimental results. The performance of the optimized controllers was evaluated according to these parameters, namely, maximum overshoot, steady-state error, settling time and root mean squared errors of the positions. Moreover, the frequency robustness analysis of the controllers was made in three cases. Findings Different simulations and experimental results were conducted to verify the control performance of the controllers. According to the comparative results of the performance, the responses of the proposed controller in simulation and experimental works are very similar. Originality/value Origin approach and origin experiment.

Causal ascription of rework in building and civil engineering projects

2014 ◽  
Vol 21 (1) ◽  
pp. 111-126 ◽  
Author(s):  
Palaneeswaran Ekambaram ◽  
Peter E.D. Love ◽  
Mohan M. Kumaraswamy ◽  
Thomas S.T. Ng
Keyword(s):  
Construction Projects ◽  
Civil Engineering ◽  
Small Data ◽  
Data Set ◽  
Content Type ◽  
Management Measures ◽  
Significant Difference ◽  
Quantitative Impact ◽  
Engineering Projects

Purpose – Rework is an endemic problem in construction projects and has been identified as being a significant factor contributing cost and schedule overruns. Causal ascription is necessary to obtain knowledge about the underlying nature of rework so that appropriate prevention mechanisms can be put in place. The paper aims to discuss these issues. Design/methodology/approach – Using a supervised questionnaire survey and case-study interviews, data from 112 building and engineering projects about the sources and causes of rework in projects were obtained. A multivariate exploration was conducted to examine the underlying relationships between rework variables. Findings – The analysis revealed that there was a significant difference between rework causes for building and civil engineering projects. The set of associations explored in the analyses will be useful to develop a generic causal model to examine the quantitative impact of rework on project performance so that appropriate prevention strategies can be identified and developed. Research limitations/implications – The limitations include: small data set (112 projects), which include 75 from building and 37 from civil engineering projects. Practical implications – Meaningful insights into the rework occurrences in construction projects will pave pathways for rational mitigation and effective management measures. Originality/value – To date there has been limited empirical research that has sought to determine the causal ascription of rework, particularly in Hong Kong.

Cold spray micro-defects and post-treatment technologies: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wang Zhizhong ◽  
Han Chao ◽  
Guosheng Huang ◽  
Han Bin ◽  
Han Bin
Keyword(s):  
Cold Spray ◽  
Influence Factors ◽  
Cold Spraying ◽  
Post Treatment ◽  
Treatment Technology ◽  
Treatment Methods ◽  
Content Type ◽  
Treatment Technologies ◽  
Single Method ◽  
Improved Performance

Purpose The deposition of particles onto a substrate during the cold spraying (CS) process relies on severe plastic deformation, so there are various micro-defects induced by insufficient deformation and severe crushing. To solve the problems, many post-treat techniques have been used to improving the quality by eliminating the micro-defects. This paper aims to help scholars and engineers in this field a better and systematic understand of CS technology by summarizing the post-treatment technologies that have been investigated recently years. Design/methodology/approach This review summarizes the types of micro-defects and introduces the effect of micro-defects on the properties of CS coating/additive manufactured, illustrates the post-treatment technologies and its effect on the microstructure and performances, and finally outlooks the future development trends of post-treatments for CS. Findings There are significant discoveries in post-treatment technology to change the performance of cold spray deposits. There are also many limitations for post-treatment methods, including improved performance and limitations of use. Thus, there is still a strong requirement for further improvement. Hybrid post-treatment may be a more ideal method, as it can eliminate more defects than a single method. The proposed ultrasonic impact treatment could be an alternative method, as it can densify and flatten the CS deposits. Originality/value It is the first time to reveal the influence factors on the performances of CS deposits from the perspective of microdefects, and proposed corresponding well targeted post-treatment methods, which is more instructive for improving the performances of CS deposits.

Knowledge management measures: an empirical investigation of Indian cement industry

2019 ◽  
Vol 26 (3) ◽  
pp. 734-752 ◽  
Author(s):  
Manish Dave ◽  
Kanhaiya Singh ◽  
Arya Kumar ◽  
Sachin Kumar
Keyword(s):  
Knowledge Management ◽  
Value Chain ◽  
Management Practices ◽  
Reliability And Validity ◽  
Cement Industry ◽  
Sales Managers ◽  
Management Tools ◽  
Content Type ◽  
Management Measures ◽  
E Mail

Purpose The purpose of this paper is to develop knowledge management constructs comprising of KM processes and KM practices through marketing and sales to derive competitive advantage (CA) in the cement industry. Design/methodology/approach A thorough and detailed analysis of the literature was carried out to develop the measures for KM practices, KM processes and their impact on CA. A total of 65 variables affecting competitiveness in the form of questionnaire were developed. The questionnaire was administered through e-mail to 962 territory sales managers (TSM) and equivalent employed in the marketing and sales function of the cement organizations in India. A total of 121 valid and complete responses were received, representing a response rate of 12.6 percent. The factor analysis was carried out on the data collected to establish reliability and validity of the measures. Findings A total of seven constructs pertaining to knowledge management practices and processes and competitiveness that comprises of 65 variables have been developed. The statistical results establish that the constructs and the variables considered in the study are reliable and valid. Research limitations/implications The sample of respondents for developing constructs consisted of TSM and equivalent employed in the marketing and sales function of cement companies in India. Research scope can be enhanced in the future study by including middle and senior level managers in cement companies to better diagnose and understand perception of KM initiatives across different levels in the cement industry. The work can also be extended to incorporate inbound logistics and procurement that directly contributes to the overall value chain to have a holistic perspective. Practical implications The measures developed in this study would be effective management tools for the implementation of knowledge management initiatives in the marketing and sales function to ascertain their level of implementation and impact on the competitiveness. Originality/value This study is probably the first of its kind in India to provide KM measures combined for practices and processes to understand the relationship with competitiveness in cement companies pertaining to marketing and sales function. It provides valuable insights as a strategic tool for investing in KM initiatives.

Optimizing the liquidity parameter of logarithmic market scoring rules prediction markets

2018 ◽  
Vol 13 (3) ◽  
pp. 736-754
Author(s):  
Suparerk Lekwijit ◽  
Daricha Sutivong
Keyword(s):  
Standard Error ◽  
Market Price ◽  
Simulation Models ◽  
Scoring Rules ◽  
Prediction Markets ◽  
Market Mechanisms ◽  
Content Type ◽  
Market Makers ◽  
True Value ◽  
Price Functions

Purpose Prediction markets are techniques to aggregate dispersed public opinions via market mechanisms to predict uncertain future events’ outcome. Many experiments have shown that prediction markets outperform other traditional forecasting methods in terms of accuracy. Logarithmic market scoring rules (LMSR) is one of the most simple and widely used market mechanisms; however, market makers have to confront crucial design decisions including the setting of the parameter “b” or the “liquidity parameter” in the price functions. As the liquidity parameter has significant effects on the market performance, this paper aims to provide a comprehensive basis for the setting of the parameter. Design/methodology/approach The analyses include the effects of the liquidity parameter on the forecast standard error and the amount of time for the market price to converge to the true value. These experiments use artificial prediction markets, the proposed simulation models that mimic real prediction markets. Findings The simulation results indicate that prediction market’s forecast standard error decreases as the value of the liquidity parameter increases. Moreover, for any given number of traders in the market, there exists an optimal liquidity parameter value that yields appropriate price adaptability and leads to the fastest price convergence. Originality/value Understanding these tradeoffs, the market makers can effectively determine the liquidity parameter value under various objectives on the standard error, the time to convergence and cost.

Coloured stochastic Petri nets modelling for the reliability and maintenance analysis of multi-state multi-unit systems

2014 ◽  
Vol 25 (4) ◽  
pp. 476-490 ◽  
Author(s):  
Zhouhang Wang ◽  
Maen Atli ◽  
H. Kondo Adjallah
Keyword(s):  
Petri Nets ◽  
Complex Structure ◽  
Real Life ◽  
Simulation Models ◽  
Decision Makers ◽  
Stochastic Petri Nets ◽  
Repairable Systems ◽  
Content Type ◽  
Markov Graphs ◽  
Maintenance Policies

Purpose – The purpose of this paper is to introduce a method for modelling the multi-state repairable systems subject to stochastic degradation processes by using the coloured stochastic Petri nets (CSPN). The method is a compact and flexible Petri nets model for multi-state repairable systems and offers an alternative to the combinatory of Markov graphs. Design/methodology/approach – The method is grounded on specific theorems used to design an algorithm for systematic construction of multi-state repairable systems models, whatever is their size. Findings – Stop and constraint functions were derived from these theorems and allow to considering k-out-of-n structure systems and to identifying the minimal cut sets, useful to monitoring the states evolution of the system. Research limitations/implications – The properties of this model will be studied, and new investigations will help to demonstrate the feasibility of the approach in real world, and more complex structure will be considered. Practical implications – The simulation models based on CSPN can be used as a tool by maintenance decision makers, for prediction of the effectiveness of maintenance strategies. Originality/value – The proposed approach and model provide an efficient tool for advanced investigations on the development and implementation of maintenance policies and strategies in real life.

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