BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Analysis and improvement of a construction permit approval process: A teaching case for developing business process development capabilities, targeting developing nations

With the increasing competitiveness in global markets, many developing nations are striving to constantly improve their services in search for the next competitive edge. As a result, the demand and need for Business Process Management (BPM) in these regions is seeing a rapid rise. Yet there exists a lack of professional expertise and knowledge to cater to that need. Therefore, the development of well-structured BPM training/ education programs has become an urgent requirement for these industries. Furthermore, the lack of textbooks or other self-educating material, that go beyond the basics of BPM, further ratifies the need for case based teaching and related cases that enable the next generation of professionals in these countries. Teaching cases create an authentic learning environment where complexities and challenges of the ‘real world’ can be presented in a narrative, enabling students to evolve crucial skills such as problem analysis, problem solving, creativity within constraints as well as the application of appropriate tools (BPMN) and techniques (including best practices and benchmarking) within richer and real scenarios. The aim of this paper is to provide a comprehensive teaching case demonstrating the means to tackle any developing nation’s legacy government process undermined by inefficiency and ineffectiveness. The paper also includes thorough teaching notes The article is presented in three main parts: (i) Introduction - that provides a brief background setting the context of this paper, (ii) The Teaching Case, and (iii) Teaching notes.

Technology adoption as a multi-stage process

This study proposes that technology adoption be considered as a multi-stage process constituting several distinct stages. Using the Theory of Planned Behaviour (TPB), Ettlie’s adoption stages and by employing data gathered from 162 owners of Small and Medium-sized Enterprises (SMEs), our findings show that the determinants of the intention to adopt packaged software fluctuate significantly across adoption stages.

Preparing engineering graduates for the knowledge economy through blended delivery of mathematics

Contemporary higher education institutions are making significant efforts to develop cohesive, meaningful and effective learning experiences for Science, Technology, Engineering and Mathematics (STEM) curricula to prepare graduates for challenges in the modern knowledge economy, thus enhancing their employability (Carnevale et al, 2011). This can inspire innovative redesign of learning experiences embedded in technology-enhanced educational environments and the development of research-informed, pedagogically reliable strategies fostering interactions between various agents of the learning-teaching process. This paper reports on the results of a project aimed at enhancing students’ learning experiences by redesigning a large, first year mathematics unit for Engineering students at a large metropolitan public university. Within the project, the current study investigates the effectiveness of selected, technology-mediated pedagogical approaches used over three semesters. Grounded in user-centred instructional design, the pedagogical approaches explored the opportunities for learning created by designing an environment containing technological, social and educational affordances. A qualitative analysis of mixed-type questionnaires distributed to students indicated important inter-relations between participants’ frames of references of the learning-teaching process and stressed the importance (and difficulty) of creating appropriate functional context. Conclusions drawn from this study may inform instructional design for blended delivery of STEM-focused programs that endeavor to enhance students’ employability by educating work-ready graduates.

Are there generalizable trends in the release of airborne synthetic clay nanoparticles from a jet milling process?

Despite recent efforts to assess the release of nanoparticles to the workplace during different nanotechnology activities, the existence of a generalizable trend in the particle release has yet to be identified. This study aimed to characterize the release of synthetic clay nanoparticles from a laboratory-based jet milling process by quantifying the variations arising from primary particle size and surface treatment of the material used, as well as the feed rate of the machine. A broad range of materials were used in this study, and the emitted particles mass (PM2.5) and number concentrations (PNC) were measured at the release source. Analysis of variance, followed by linear mixed-effects modeling, was applied to quantify the variations in PM2.5 and PNC of the released particles caused by the abovementioned factors. The results confirmed that using materials of different primary size and surface treatment affects the release of the particles from the same process by causing statistically-significant variations in PM2.5 and PNC. The interaction of these two factors should also be taken into account as it resulted in variations in the measured particles release properties. Furthermore, the feed rate of the milling machine was confirmed to be another influencing parameter. Although this research does not identify a specific pattern in the release of synthetic clay nanoparticles from the jet milling process generalizable to other similar settings, it emphasizes that each tested case should be handled individually in terms of exposure considerations.

Prediction of shrinkage and porosity during drying: Considering both material properties and process conditions

Drying of food materials offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Shrinkage and variations in porosity are the common micro and microstructural changes that take place during the drying of mostly the food materials. Although extensive research has been carried out on the prediction of shrinkage and porosity over the time of drying, no single model exists which consider both material properties and process condition in the same model. In this study, an attempt has been made to develop and validate shrinkage and porosity models of food materials during drying considering both process parameters and sample properties. The stored energy within the sample, elastic potential energy, glass transition temperature and physical properties of the sample such as initial porosity, particle density, bulk density and moisture content have been taken into consideration. Physical properties and validation have been made by using a universal testing machine ( Instron 2kN), a profilometer (Nanovea) and a pycnometer. Apart from these, COMSOL Multiphysics 4.4 has been used to solve heat and mass transfer physics. Results obtained from models of shrinkage and porosity is quite consistent with the experimental data. Successful implementation of these models would ensure the use of optimum energy in the course of drying and better quality retention of dried foods.

A summary of the 'Engineering Education for Sustainable Development:Toolkit of Information & Teaching Material'

This paper reflects on the critical need for an urgent transformation of higher education curriculum globally, to equip society with professionals who can address our 21st Century sustainable living challenges. Specifically it discusses a toolkit called the ‘Engineering Sustainable Solutions Program’, which is a freely available, rigorously reviewed and robust content resource for higher education institutions to access content on innovations and opportunities in the process of evolving the curriculum...

Revising history for cost-informed process improvement

Organisations are constantly seeking new ways to improve operational efficiencies. This study investigates a novel way to identify potential efficiency gains in business operations by observing how they were carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how these trade-offs can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A number of optimisation techniques are proposed to explore and assess alternative execution scenarios. The objective function is represented by a cost structure that captures different process dimensions. An experimental evaluation is conducted to analyse the performance and scalability of the optimisation techniques: integer linear programming (ILP), hill climbing, tabu search, and our earlier proposed hybrid genetic algorithm approach. The findings demonstrate that the hybrid genetic algorithm is scalable and performs better compared to other techniques. Moreover, we argue that the use of ILP is unrealistic in this setup and cannot handle complex cost functions such as the ones we propose. Finally, we show how cost-related insights can be gained from improved execution scenarios and how these can be utilised to put forward recommendations for reducing process-related cost and overhead within organisations.

Evaluating and predicting overall process risk using event logs

Companies standardise and automate their business processes in order to improve process eff ciency and minimise operational risks. However, it is di fficult to eliminate all process risks during the process design stage due to the fact that processes often run in complex and changeable environments and rely on human resources. Timely identification of process risks is crucial in order to insure the achievement of process goals. Business processes are often supported by information systems that record information about their executions in event logs. In this article we present an approach and a supporting tool for the evaluation of the overall process risk and for the prediction of process outcomes based on the analysis of information recorded in event logs. It can help managers evaluate the overall risk exposure of their business processes, track the evolution of overall process risk, identify changes and predict process outcomes based on the current value of overall process risk. The approach was implemented and validated using synthetic event logs and through a case study with a real event log.

The rapid manufacture of uniform composite multicellular-biomaterial micropellets, their assembly into macroscopic organized tissues, and potential applications in cartilage tissue engineering

We and others have published on the rapid manufacture of micropellet tissues, typically formed from 100-500 cells each. The micropellet geometry enhances cellular biological properties, and in many cases the micropellets can subsequently be utilized as building blocks to assemble complex macrotissues. Generally, micropellets are formed from cells alone, however when replicating matrix-rich tissues such as cartilage it would be ideal if matrix or biomaterials supplements could be incorporated directly into the micropellet during the manufacturing process. Herein we describe a method to efficiently incorporate donor cartilage matrix into tissue engineered cartilage micropellets. We lyophilized bovine cartilage matrix, and then shattered it into microscopic pieces having average dimensions < 10 μm diameter; we termed this microscopic donor matrix "cartilage dust (CD)". Using a microwell platform, we show that ~0.83 μg CD can be rapidly and efficiently incorporated into single multicellular aggregates formed from 180 bone marrow mesenchymal stem/stromal cells (MSC) each. The microwell platform enabled the rapid manufacture of thousands of replica composite micropellets, with each micropellet having a material/CD core and a cellular surface. This micropellet organization enabled the rapid bulking up of the micropellet core matrix content, and left an adhesive cellular outer surface. This morphological organization enabled the ready assembly of the composite micropellets into macroscopic tissues. Generically, this is a versatile method that enables the rapid and uniform integration of biomaterials into multicellular micropellets that can then be used as tissue building blocks. In this study, the addition of CD resulted in an approximate 8-fold volume increase in the micropellets, with the donor matrix functioning to contribute to an increase in total cartilage matrix content. Composite micropellets were readily assembled into macroscopic cartilage tissues; the incorporation of CD enhanced tissue size and matrix content, but did not enhance chondrogenic gene expression.

Consultation: Energy efficiency and engineering education

This report provides the Commonwealth Department of Resources, Energy and Tourism (RET) with a summary of consultation undertaken with representatives from industry and academia around Australia regarding mainstreaming energy efficiency within engineering education. Specifically, the report documents the purpose of the consultation process, key messages and emerging themes, industry-perceived gaps in energy efficiency related knowledge and skills, and academic considerations regarding graduate attributes and learning pathways to close these gaps. This information complements previous reports by presenting the current thoughts and ideas of more than 100 engineering academic and practising professionals who are actively involved in building capacity through the education system or implementing energy efficiency improvements in companies/the workplace. Furthermore, the report describes the emergence of a potential ‘community of practice’ in energy efficiency capacity building that arose during the project.

Implementing process views in the web service environment

Web service and business process technologies are widely adopted to facilitate business automation and collaboration. Given the complexity of business processes, it is a sought-after feature to show a business process with different views to cater for the diverse interests, authority levels, etc., of different users. Aiming to implement such flexible process views in the Web service environment, this paper presents a novel framework named FlexView to support view abstraction and concretisation of WS-BPEL processes. In the FlexView framework, a rigorous view model is proposed to specify the dependency and correlation between structural components of process views with emphasis on the characteristics of WS-BPEL, and a set of rules are defined to guarantee the structural consistency between process views during transformations. A set of algorithms are developed to shift the abstraction and concretisation operations to the operational level. A prototype is also implemented for the proof-of-concept purpose. © 2010 Springer Science+Business Media, LLC.

Linking business goals to process models in semantic business process modeling

Broad knowledge is required when a business process is modeled by a business analyst. We argue that existing Business Process Management methodologies do not consider business goals at the appropriate level. In this paper we present an approach to integrate business goals and business process models. We design a Business Goal Ontology for modeling business goals. Furthermore, we devise a modeling pattern for linking the goals to process models and show how the ontology can be used in query answering. In this way, we integrate the intentional perspective into our business process ontology framework, enriching the process description and enabling new types of business process analysis. © 2008 IEEE.

Incorporating process variability into stormwater quality modelling

Process variability in pollutant build-up and wash-off generates inherent uncertainty that affects the outcomes of stormwater quality models. Poor characterisation of process variability constrains the accurate accounting of the uncertainty associated with pollutant processes. This acts as a significant limitation to effective decision making in relation to stormwater pollution mitigation. The study undertaken developed three theoretical scenarios based on research findings that variations in particle size fractions <150µm and >150µm during pollutant build-up and wash-off primarily determine the variability associated with these processes. These scenarios, which combine pollutant build-up and wash-off processes that takes place on a continuous timeline, are able to explain process variability under different field conditions. Given the variability characteristics of a specific build-up or wash-off event, the theoretical scenarios help to infer the variability characteristics of the associated pollutant process that follows. Mathematical formulation of the theoretical scenarios enables the incorporation of variability characteristics of pollutant build-up and wash-off processes in stormwater quality models. The research study outcomes will contribute to the quantitative assessment of uncertainty as an integral part of the interpretation of stormwater quality modelling outcomes.

Mining process risks and resource profiles

This research contributes novel techniques for identifying and evaluating business process risks and analysing human resource behaviour. The developed techniques use predefined indicators to identify process risks in individual process instances, evaluate overall process risk, predict process outcomes and analyse human resource behaviour based on the analysis of information about process executions recorded in event logs by information systems. The results of this research can help managers to more accurately evaluate the risk exposure of their business processes, to more objectively evaluate the performance of their employees, and to identify opportunities for improvement of resource and process performance.