Challenges and Opportunities for Simulation Modelling Integrating Mine Haulage and Truck Shop Operations

Historically considerable work has been done to develop models that simulate truck haulage for both underground and open-pit operations. However, this work frequently simplifies or overlooks aspects such as the reliability of the trucks, priority setting and maintenance strategies in the truck shop, and resourcing of the repair facilities. This paper provides an overview of work in this area that is specific to the mining industry and also relevant work from other sectors that might inform how improvements can be made. The paper proposes some specific projects that will assist in identifying technical issues. Initially, it is important to understand what questions should be asked, and justify why it is worth going to the trouble of building a simulation model. What are the potential benefits? How do we measure the performance of the whole system? Once these are resolved, what are the challenges in incorporating asset management strategy, condition and reliability related data into the truck haulage simulation model? These issues will be explored and suggestions for future projects presented with examples

Dynamic safety capability and management systems: An assessment tool to evaluate the “fitness-to-operate” in high-risk industrial environments

Aim: The paper outlines a systemic approach to understanding and assessing safety capability in high-risk industries, like off-shore oil, gas industry, chemical operators. The "Fitness to Operate" framework (acronym: FTO) (Griffin et al., 2014) has been recently defined by three enabling capitals that create safety capability: organizational capital, social capital, and human capital. Furthermore, each type of capital is identified by more specific dimensions based on current theories of safety, management, and organizational processes. In this paper, we will present a multidimensional assessment tool that offers a comprehensive picture of safety capability by real industrial operators in order to understand and evaluate their "fitness-to-operate" (FTO). Method: This current paper aims to describe the multi-phase development process of a FTO assessment tool in the format of a multidimensional survey questionnaire. A) The first research phase consists of the item generation of a large prototype pool with about 200 contents-items covering the 27 dimensions of the conceptual representation of the FTO framework. This initial pool was developed by a team of academic researchers, through a deductive process, and in the light of the original FTO conceptualization, as defined by Griffin and colleagues (2014) B) In a second research phase, the initial pools of items were re-examined by a new pool of academic researchers, assessing the quality of the contents, and in order to refine the extensive version of the prototype, eliminating potential redundancies and inadequate items. C) In a third phase with structured interviews to a pool of industrial experts (senior safety managers; senior executives), the authors assessed the quality of the prototype tool developed by the academic researchers, in order to evaluate and ranks the items of the prototype in term of quality, in order to define and identify a shorter version of the prototype. All the items were assessed by the experts considering criteria such as: i) relevance ii) clearness iii) verifiability iv) specificity v) ease of answer. Implications: Overall, the FTO assessment tool enables a comprehensive coverage of factors that influence short-term and long-term safety outcomes. The tool may serve to help safety regulators and industrial operators to understand, assess, and eventually implement and improve the safety capability and fitness-to-operate in complex industrial and organizational context

Data-driven reliability analysis of Boeing 787 Dreamliner

The Boeing 787 Dreamliner, launched in 2011, was presented as a game changer in air travel. With the aim of producing an efficient, mid-size, wide-body plane, Boeing initiated innovations in product and process design, supply chain operation, and risk management. Nevertheless, there were reliability issues from the start, and the plane was grounded by the U.S. Federal Aviation Administration (FAA) in 2013, due to safety problems associated with Li-ion battery fires. This paper chronicles events associated with the aircraft's initial reliability challenges. The manufacturing, supply chain, and organizational factors that contributed to these problems are assessed based on FAA data. Recommendations and lessons learned are provided for the benefit of engineers and managers who will be engaged in future complex systems development

A vibration cavitation sensitivity parameter based on spectral and statistical methods

Cavitation is one of the main problems reducing the longevity of centrifugal pumps in industry today. If the pump operation is unable to maintain operating conditions around the best efficiency point, it can be subject to conditions that may lead to vaporisation or flashing in the pipes upstream of the pump. The implosion of these vapour bubbles in the impeller or volute causes damaging effects to the pump. A new method of vibration cavitation detection is proposed in this paper, based on adaptive octave band analysis, principal component analysis and statistical metrics. Full scale industrial pump efficiency testing data was used to determine the initial cavitation parameters for the analysis. The method was then tested using vibration measured from a number of industry pumps used in the water industry. Results were compared to knowledge known about the state of the pump, and the classification of the pump according to ISO 10816

The physical fitness profiles of specialist policing teams

Aim: To profile the fitness of two groups of Australian Specialist Police.Design: Retrospective Cohort StudyMethod: De-identified data of 17 male specialist police officers from two specialist police response groups (Riot Squad (RS) and Police Tactical Group (PTG)) were provided. Data included demographics (age, height, and weight), strength (1 Repetition Maximum (1RM) bench press, deadlift, pull-up + Body Weight (BW), and squat), speed (0-10m acceleration & 10-20m peak velocity), agility (box agility drill), aerobic capacity (30-15 Intermittent Fitness Test) and power (bench throw and countermovement jump).Results: There were no significant differences in demographics, although officers from RS were, on average, older (1.45yrs, p=0.390), shorter (-2.04cm, p=0.15), and lighter (-3.43kg, p=0.55) than PTG officers. PTG officers had significantly greater strength (1RM deadlift = 38.50kg, p= 0.001, 95% CI [17.62-59.38], 1RM squat = 34.00kg, p< 0.001, 95% CI [16.6-51.5], 1RM bench press = 26.83kg, p=0.004, 95% CI [9.8-43.8]) andquicker acceleration (0.11sec, p=0.032, 95% CI [0.01-0.21]) than RS officers. Both groups performed at a level comparable to elite athletes for most other measures.Conclusion: Specialist police possess high levels of aerobic fitness, strength, acceleration, and power, with subtle differences between units, thought to be due to varying occupational roles. This study provides benchmarks for selection, return-to-work practices and maintenance programs for health professionals working within these units

Detecting Asset Cascading Failures Using Complex Network Analysis

Experienced process plant personnel observe that corrective maintenance work on one asset may often be followed by corrective work on the same asset or connected assets within a short amount of time. This problem is referred to as a cascading failure. Confirming if these events are chronic is difficult given the number of assets and the volume of maintenance and operation data. If cascading events can be identified, preventative measures can be implemented to prevent those cascades, eliminating unnecessary corrective work. This project uses complex network analysis to identify cascading events and where co-occurrence of work is most frequent, in a process plant. Data is drawn from over 50,000 work orders for 5,655 pumps in a mining company over a five-year period. A complex network is produced by connecting assets based on the frequency of co-occurrence of work. Beside the advantages of the visualisation of complex networks, the method produces quantified measures, normalised degree, eigenvector centrality and betweenness centrality, which are used to identify assets with significant impact on other assets. Affected pumps are apparent as communities in the network. This analysis identifies pumps that are 'super-spreaders': pumps who experience corrective maintenance events which lead to corrective maintenance events on other pumps. The model can be tuned to different time windows, for example events within one or seven days. From these insights, changes can be made to operational, maintenance and recording practices to prevent re-occurrence. Of particular note in this data was the occurrence of self-loops in certain pumps and the prevalence of hidden failures in standby pumps

Rethinking Maintenance Terminology for an Industry 4.0 Future

Sensors and mathematical models have been used since the 1990’s to assess the health of systems and diagnose anomalous behavior. The advent of the Internet of Things (IoT) increases the range of assets on which data can be collected cost effectively. Cloud-computing and the wider availability of data and models are democratizing the implementation of prognostic health (PHM) technologies. Together, these advancements and other Industry 4.0 developments are creating a paradigm shift in how maintenance work is planned and executed. In this new future, maintenance will be initiated once a potential failure has been detected (using PHM) and thus completed before a functional failure has occurred. Thus corrective work is required since corrective work is defined as “work done to restore the function of an asset after failure or when failure is imminent.” Many metrics for measuring the effectiveness of maintenance work management are grounded in a negative perspective of corrective work and do not clearly capture work arising from condition monitoring and predictive modeling investments. In this paper, we use case studies to demonstrate the need to rethink maintenance terminology. The outcomes of this work include 1) definitions to be used for consistent evaluation of work management performance in an Industry 4.0 future and 2) recommendations to improve detection of work related to PHM activities

IoT-Based Prognostics and Systems Health Management for Industrial Applications

Prognostics and systems health management (PHM) is an enabling discipline that uses sensors to assess the health of systems, diagnoses anomalous behavior, and predicts the remaining useful performance over the life of the asset. The advent of the Internet of Things (IoT) enables PHM to be applied to all types of assets across all sectors, thereby creating a paradigm shift that is opening up significant new business opportunities. This paper introduces the concepts of PHM and discusses the opportunities provided by the IoT. Developments are illustrated with examples of innovations from manufacturing, consumer products, and infrastructure. From this review, a number of challenges that result from the rapid adoption of IoT-based PHM are identified. These include appropriate analytics, security, IoT platforms, sensor energy harvesting, IoT business models, and licensing approaches.clos

A conceptual framework and practical guide for assessing fitness-to-operate in the offshore oil and gas industry

The paper outlines a systemic approach to understanding and assessing safety capability in the offshore oil and gas industry. We present a conceptual framework and assessment guide for understanding fitness-to-operate (FTO) that builds a more comprehensive picture of safety capability for regulators and operators of offshore facilities. The FTO framework defines three enabling capitals that create safety capability: organizational capital, social capital, and human capital. For each type of capital we identify more specific dimensions based on current theories of safety, management, and organizational processes. The assessment guide matches specific characteristics to each element of the framework to support assessment of safety capability. The content and scope of the FTO framework enable a more comprehensive coverage of factors that influence short-term and long-term safety outcomes

ieee access special section editorial intelligent systems for the internet of things

The underlying concept of the Internet of Things (IoT) is simply to connect all devices and systems together via the Internet so that more suitable services can be provided to users. Many infrastructures, systems, and devices of the IoT have matured while some are still being developed. This is why several recent studies have claimed that IoT will dramatically change our lives. Today, we can find research topics driven by IoT technologies and can imagine that the era of smart homes and cities will be coming in the foreseeable future. The development of the IoT has reached a crossroad. One of the current research trends is to make this kind of system smarter, by using intelligent technologies to provide a much more convenient environment for humans. Among the intelligent technologies, how to handle the massive amount of data generated by the systems and devices of the IoT has been widely considered. Many other technologies, such as data mining, big data analytics, statistical and other analysis technologies, have also been used for analyzing data generated from the IoT. In addition to the analysis technologies, intelligent system technologies also provide many possibilities for the IoT because they can be used to enhance not only the performance of a system and its devices, but they can also be aware of events that have occurred