Reliability analysis of underground mining equipment using genetic algorithms

2014 ◽  
Vol 20 (1) ◽  
pp. 32-50 ◽  
Author(s):  
Nick Vayenas ◽  
Sihong Peng
Keyword(s):  
Reliability Analysis ◽  
Case Studies ◽  
Reliability Assessment ◽  
Real Life ◽  
Software Tool ◽  
Mining Equipment ◽  
Data Set ◽  
Content Type ◽  
Reliability Centered Maintenance ◽  
Potential Applications

Purpose – While increased mechanization and automation make considerable contributions to mine productivity, unexpected equipment failures and imperfect planned or routine maintenance prohibit the maximum possible utilization of sophisticated mining equipment and require significant amount of extra capital investment. Traditional preventive/planned maintenance is usually scheduled at a fixed interval based on maintenance personnel's experience and it can result in decreasing reliability. This paper deals with reliability analysis and prediction for mining machinery. A software tool called GenRel is discussed with its theoretical background, applied algorithms and its current improvements. In GenRel, it is assumed that failures of mining equipment caused by an array of factors (e.g. age of equipment, operating environment) follow the biological evolution theory. GenRel then simulates the failure occurrences during a time period of interest based on Genetic Algorithms (GAs) combined with a number of statistical procedures. The paper also discusses a case study of two mine hoists. The purpose of this paper is to investigate whether or not GenRel can be applied for reliability analysis of mine hoists in real life. Design/methodology/approach – Statistical testing methods are applied to examine the similarity between the predicted data set with the real-life data set in the same time period. The data employed in this case study is compiled from two mine hoists from the Sudbury area in Ontario, Canada. Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation. Findings – The case studies shown in this paper demonstrate successful applications of a GAs-based software, GenRel, to analyze and predict dynamic reliability characteristics of two hoist systems. Two separate case studies in Mine A and Mine B at a time interval of three months both present acceptable prediction results at a given level of confidence, 5 percent. Practical implications – Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation. Originality/value – Compared to conventional mathematical models, GAs offer several key advantages. To the best of the authors’ knowledge, there has not been a wide application of GAs in hoist reliability assessment and prediction. In addition, the authors bring discrete distribution functions to the software tool (GenRel) for the first time and significantly improve computing efficiency. The results of the case studies demonstrate successful application of GenRel in assessing and predicting hoist reliability, and this may lead to better preventative maintenance management in the industry.

scholarly journals Maintainability Analysis of Underground Mining Equipment Using Genetic Algorithms: Case Studies with an LHD Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Sihong Peng ◽  
Nick Vayenas
Keyword(s):  
Genetic Algorithms ◽  
Case Studies ◽  
Underground Mining ◽  
Real Life ◽  
Mining Equipment ◽  
Data Set ◽  
Life Data ◽  
Time Period ◽  
Real Life Data ◽  
Maintainability Analysis

While increased mine mechanization and automation make considerable contributions to mine productivity, unexpected equipment failures and planned or routine maintenance prohibit the maximum possible utilization of sophisticated mining equipment and require a significant amount of extra capital investment. This paper deals with aspects of maintainability prediction for mining machinery. A PC software called GenRel was developed for this purpose. In GenRel, it is assumed that failures of mining equipment caused by an array of factors follow the biological evolution theory. GenRel then simulates the failure occurrences during a time period of interest using genetic algorithms (GAs) coupled with a number of statistical techniques. A group of case studies focuses on maintainability analysis of a Load Haul Dump (LHD) vehicle with two different time intervals, three months and six months. The data was collected from an underground mine in the Sudbury area in Ontario, Canada. In each prediction case study, a statistical test is carried out to examine the similarity between the predicted data set with the real-life data set in the same time period. The objectives of case studies include an assessment of the applicability of GenRel using real-life data and an investigation of the impacts of data size and chronological sequence on prediction results.

Viewing organised crime and terrorist organisations through the financial threats they pose to society

2018 ◽  
Vol 25 (4) ◽  
pp. 940-950
Author(s):  
Thomas Ren
Keyword(s):  
Case Studies ◽  
Design Methodology ◽  
Conceptual Models ◽  
Real Life ◽  
Organised Crime ◽  
Meaningful Difference ◽  
Content Type ◽  
Financial Perspective ◽  
Enterprise Theory

Purpose The purpose of this paper is to examine whether there is a meaningful difference, viewed from a financial perspective, in distinguishing between organised crime and terrorist organisations, with regard to the control and mitigation of the threats that they pose to society. Design/methodology/approach The paper uses conceptual models obtained from enterprise theory and economics, as well as criminology, and makes use of case studies through the application of these models. Findings The paper finds that when viewed from a financial perspective, there is no meaningful difference in distinguishing between the groups because many have undergone processes of convergence and transformation, such that they assume each other’s operational and motivational characteristics. However, the answer also depends on how precisely one defines each type of illicit group as well as the transitions they undergo. Originality/value The value of this paper is that it applies two separate models on interactions between organised crime and terrorist organisations, the terror–crime continuum and interaction spectrum, to real life situations. After assessing their validity for more recent examples of such illicit groups, it then provides a balanced argument as to distinguishing between organised crime and terrorism. One limitation towards the paper’s originality, however, is that it draws mainly from pre-existing literature.

Dynamic testing resource allocation modeling for multi-release software using optimal control theory and genetic algorithm

2020 ◽  
Vol 37 (6/7) ◽  
pp. 1049-1069
Author(s):  
Vijay Kumar ◽  
Ramita Sahni
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Resource Allocation ◽  
Real Life ◽  
Theoretic Approach ◽  
Numerical Illustration ◽  
Data Set ◽  
Allocation Model ◽  
Content Type ◽  
Software Firms

PurposeThe use of software is overpowering our modern society. Advancement in technology is directly proportional to an increase in user demand which further leads to an increase in the burden on software firms to develop high-quality and reliable software. To meet the demands, software firms need to upgrade existing versions. The upgrade process of software may lead to additional faults in successive versions of the software. The faults that remain undetected in the previous version are passed on to the new release. As this process is complicated and time-consuming, it is important for firms to allocate resources optimally during the testing phase of software development life cycle (SDLC). Resource allocation task becomes more challenging when the testing is carried out in a dynamic nature.Design/methodology/approachThe model presented in this paper explains the methodology to estimate the testing efforts in a dynamic environment with the assumption that debugging cost corresponding to each release follows learning curve phenomenon. We have used optimal control theoretic approach to find the optimal policies and genetic algorithm to estimate the testing effort. Further, numerical illustration has been given to validate the applicability of the proposed model using a real-life software failure data set.FindingsThe paper yields several substantive insights for software managers. The study shows that estimated testing efforts as well as the faults detected for both the releases are closer to the real data set.Originality /valueWe have proposed a dynamic resource allocation model for multirelease of software with the objective to minimize the total testing cost using the flexible software reliability growth model (SRGM).

Site planning and design of green residential building projects: case studies in China

2019 ◽  
Vol 27 (2) ◽  
pp. 525-543
Author(s):  
Xiaosen Huo ◽  
Ann Tit Wan Yu ◽  
Wu Zezhou ◽  
Wadu Mesthrige Jayantha
Keyword(s):  
Case Studies ◽  
Questionnaire Survey ◽  
Residential Buildings ◽  
Real Life ◽  
Green Building ◽  
Green Buildings ◽  
Building Projects ◽  
Content Type ◽  
Planning And Design ◽  
Site Planning

Purpose The purpose of this paper is to present site planning and design (SPD) relevant variables and items in practice for practitioners to better understand and implement SPD in green building projects. Design/methodology/approach The research methods include questionnaire survey and case studies in the context of China. A questionnaire survey was adopted to identify the importance of 13 variables and the corresponding 38 items in SPD of green residential buildings. Three green residential projects including one in Hong Kong and two in Mainland China were selected to investigate the SPD considerations in practice and to discuss the necessary improvement. Findings The results show that 12 out of the 13 variables of SPD in green buildings are involved in the three case projects to some extent, thereby underscore the importance of these variables. The potential improvement in real-life SPD of green buildings is also discussed such as adopting design-build and integrated project delivery methods and preserving and protecting cultural characteristics on site. Originality/value The research findings may serve as a reference for practitioners to better conduct SPD in green building projects.

Brand intrapreneurs and brand managers: in search of disruption

2014 ◽  
Vol 35 (4) ◽  
pp. 29-36 ◽  
Author(s):  
Deryck J. van Rensburg
Keyword(s):  
Case Studies ◽  
Data Gathering ◽  
Real Life ◽  
High Growth ◽  
Content Type ◽  
Multiple Variables ◽  
Entrepreneurial Action ◽  
Life Phenomena ◽  
Brand Portfolios ◽  
Internal Venturing

Purpose – The paper aims to postulate as to whether the brand manager function and role is best placed for creating high growth, disruptive brand portfolios. As a potential solution toward resolving this, prescriptions for nurturing brand intrapreneurs are advanced to accelerate corporate entrepreneurial thinking and action based on the empirical case material. Design/methodology/approach – This paper draws from seven case studies of six large global consumer packaged goods (CPG) firms involved in strategic brand venturing activity. Interview quotations are used to provide an invocative account of key ideas and arguments in the paper. Data gathering comprised extensive documentation and observation, and 21 semistructured interviews with senior-level executives and entrepreneurs. Interviews ranged in length with a mean interview time of 1 hour 23 minutes. All interviews were recorded with interviewee permission and, subsequently, transcribed and analyzed. Within-case and across-case analyses were performed using the spiral methodology espoused by Creswell (2007). Findings – Findings are clustered under three themes: galvanic and savvy leaders, entrepreneurial program design and nuanced operating models. In particular, the simultaneous practice of external and internal venturing inside a single venturing unit was noted to generate unique learning and promote corporate entrepreneurial action. Research limitations/implications – While case studies offer a way of investigating complex real-life phenomena with multiple variables, their ideographic nature suffers from an inability to generalize findings to other populations. This research design is no different. Nevertheless, rigorous within-case and cross-case analyses were performed involving world-class CPG marketing corporations to arrive at the findings presented. Practical implications – Numerous prescriptions for implementing brand intrapreneurship are advanced in the paper. Originality/value – Although technology venturing is a well-researched topic, ambidextrous brand venturing groups among CPG corporations renown for their marketing and branding prowess are only beginning to catch-on in practice – this is one of the first empirical paper to enumerate the practices of brand intrapreneurship within a strategic brand venturing framework.

scholarly journals 4D printing – revolution or fad?

2014 ◽  
Vol 34 (2) ◽  
pp. 123-127 ◽  
Author(s):  
Eujin Pei
Keyword(s):  
Case Studies ◽  
Smart Materials ◽  
State Of The Art ◽  
The State ◽  
Additive Manufacture ◽  
4D Printing ◽  
Content Type ◽  
Potential Applications ◽  
Manufacturing Technologies ◽  
Review State

Purpose – This feature article aims to review state-of-the-art developments in additive manufacture, in particular, 4D printing. It discusses what it is, what research has been carried out and maps potential applications and its future impact. Design/methodology/approach – The article first defines additive manufacturing technologies and goes on to describe the state-of-the-art. Following which the paper examines several case studies and maps a trend that shows an emergence of 4D printing. Findings – The case studies highlight a particular specialization within additive manufacture where the use of adaptive, biomimetic composites can be programmed to reshape, or have embedded properties or functionality that transform themselves when subjected to external stimuli. Originality/value – This paper discusses the state-of-the-art of additive manufacture, discussing strategies that can be used to reduce the print process (such as through kinematics); and the use of smart materials where parts adapt themselves in response to the surrounding environment supporting the notion of self-assemblies.

Empirical study on the effect of using synthetic attributes on classification algorithms

2017 ◽  
Vol 10 (2) ◽  
pp. 111-129 ◽  
Author(s):  
Ali Hasan Alsaffar
Keyword(s):  
Data Mining ◽  
Empirical Study ◽  
Student Performance ◽  
Software Tool ◽  
Real Data ◽  
Support Vector ◽  
Classification Algorithms ◽  
Past Performance ◽  
Data Set ◽  
Content Type

Purpose The purpose of this paper is to present an empirical study on the effect of two synthetic attributes to popular classification algorithms on data originating from student transcripts. The attributes represent past performance achievements in a course, which are defined as global performance (GP) and local performance (LP). GP of a course is an aggregated performance achieved by all students who have taken this course, and LP of a course is an aggregated performance achieved in the prerequisite courses by the student taking the course. Design/methodology/approach The paper uses Educational Data Mining techniques to predict student performance in courses, where it identifies the relevant attributes that are the most key influencers for predicting the final grade (performance) and reports the effect of the two suggested attributes on the classification algorithms. As a research paradigm, the paper follows Cross-Industry Standard Process for Data Mining using RapidMiner Studio software tool. Six classification algorithms are experimented: C4.5 and CART Decision Trees, Naive Bayes, k-neighboring, rule-based induction and support vector machines. Findings The outcomes of the paper show that the synthetic attributes have positively improved the performance of the classification algorithms, and also they have been highly ranked according to their influence to the target variable. Originality/value This paper proposes two synthetic attributes that are integrated into real data set. The key motivation is to improve the quality of the data and make classification algorithms perform better. The paper also presents empirical results showing the effect of these attributes on selected classification algorithms.

scholarly journals Predicting voluntary turnover through human resources database analysis

2018 ◽  
Vol 41 (1) ◽  
pp. 96-112 ◽  
Author(s):  
Evy Rombaut ◽  
Marie-Anne Guerry
Keyword(s):  
Logistic Regression ◽  
Decision Tree ◽  
Human Resources ◽  
Real Life ◽  
Model Performance ◽  
Voluntary Turnover ◽  
Private Company ◽  
Data Set ◽  
Content Type ◽  
Individual Level

Purpose This paper aims to question whether the available data in the human resources (HR) system could result in reliable turnover predictions without supplementary survey information. Design/methodology/approach A decision tree approach and a logistic regression model for analysing turnover were introduced. The methodology is illustrated on a real-life data set of a Belgian branch of a private company. The model performance is evaluated by the area under the ROC curve (AUC) measure. Findings It was concluded that data in the personnel system indeed lead to valuable predictions of turnover. Practical implications The presented approach brings determinants of voluntary turnover to the surface. The results yield useful information for HR departments. Where the logistic regression results in a turnover probability at the individual level, the decision tree makes it possible to ascertain employee groups that are at risk for turnover. With the data set-based approach, each company can, immediately, ascertain their own turnover risk. Originality/value The study of a data-driven approach for turnover investigation has not been done so far.

Construction project productivity evaluation framework with expanded system boundaries

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wenting Zhan ◽  
Wei Pan ◽  
Le Chen
Keyword(s):  
Hong Kong ◽  
Case Studies ◽  
Construction Industry ◽  
Construction Projects ◽  
Construction Project ◽  
Real Life ◽  
Evaluation Framework ◽  
Two Stage ◽  
System Boundaries ◽  
Content Type

PurposeWhile the investment in construction projects has increased over the past few decades, low construction project productivity (CPP) appeared to be persistent, thereby reflecting an “investment-in-failure” paradox between the investment and CPP. Hence, this paper aims to develop a systematic and holistic CPP evaluation framework to explain the apparent paradox in the construction industry.Design/methodology/approachThe paper first reviews the literature about the theories of system, production, principal–agent and project success evaluation to re-conceptualise the CPP and proposes a two-stage CPP evaluation framework. The framework is subsequently explored through a sequential qualitative mixed-methods design within the context of the Hong Kong construction industry by combining 32 semi-structured interviews with senior industry experts and exploratory case studies, with three real-life construction projects.FindingsThe paper identifies three system boundaries for CPP evaluation, that is, parameter, timeframe and stakeholder, and develops a two-stage CPP evaluation framework to indicate site efficiency and utilisation effectiveness, thereby accessing the productivity of both the construction and post-construction stages. The “investment-in-failure” paradox associated with current CPP evaluation approaches is primarily attributed to the narrowly defined CPP boundaries.Research limitations/implicationsThe qualitative exploration of the evaluation framework only focusses on the Hong Kong construction industry. Further case studies within other urban contexts could be used to improve the generalisability of the findings. Quantitative research is also necessary to advance theoretical development of the two-stage CPP evaluation.Practical implicationsThe systemic CPP conceptualisation and the two-stage CPP evaluation framework support the systems thinking of industry stakeholders and enable them to formulate holistic strategies for long-term CPP enhancement.Originality/valueThe research demonstrates the needs to expand the system boundaries of CPP to reflect its systemic value and to shift the paradigm of CPP evaluation from being output-orientated and quantity-focussed to being outcome-orientated and value-focussed.

scholarly journals Multiple-Membership Survival Analysis and Its Applications in Organizational Behavior and Management Research

2019 ◽  
pp. 109442811987745
Author(s):  
Hans Tierens ◽  
Nicky Dries ◽  
Mike Smet ◽  
Luc Sels
Keyword(s):  
Organizational Behavior ◽  
Large Scale ◽  
Model Building ◽  
Real Life ◽  
Hierarchical Structures ◽  
Survival Model ◽  
Survival Models ◽  
Data Set ◽  
Potential Applications ◽  
Multiple Membership

Multilevel paradigms have permeated organizational research in recent years, greatly advancing our understanding of organizational behavior and management decisions. Despite the advancements made in multilevel modeling, taking into account complex hierarchical structures in data remains challenging. This is particularly the case for models used for predicting the occurrence and timing of events and decisions—often referred to as survival models. In this study, the authors construct a multilevel survival model that takes into account subjects being nested in multiple environments—known as a multiple-membership structure. Through this article, the authors provide a step-by-step guide to building a multiple-membership survival model, illustrating each step with an application on a real-life, large-scale, archival data set. Easy-to-use R code is provided for each model-building step. The article concludes with an illustration of potential applications of the model to answer alternative research questions in the organizational behavior and management fields.

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