Managing risk in process-aware information systems

This research contributes a fully-operational approach for managing business process risk in near real-time. The approach consists of a language for defining risks on top of process models, a technique to detect such risks as they eventuate during the execution of business processes, a recommender system for making risk-informed decisions, and a technique to automatically mitigate the detected risks when they are no longer tolerable. Through the incorporation of risk management elements in all stages of the lifecycle of business processes, this work contributes to the effective integration of the fields of Business Process Management and Risk Management.

Managing knowledge for asset management : shifting from process to relational frames

The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the knowledge management field have showed that relational modes such as social capital is imperative for ef-fective KM outcomes. In this paper, we argue that incorporating a relational ap-proach to KM is more likely to contribute to the exchange of ideas and the devel-opment of creative responses necessary to improve decision-making in asset management. This conceptual paper uses extant literature to explain knowledge management antecedents and explore its outcomes in the context of asset man-agement. KM is a component in the new Integrated Strategic Asset Management (ISAM) framework developed in conjunction with asset management industry as-sociations (AAMCoG, 2012) that improves asset management performance. In this paper we use Nahapiet and Ghoshal’s (1998) model to explain antecedents of relational approach to knowledge management. Further, we develop an argument that relational knowledge management is likely to contribute to the improvement of the ISAM framework components, such as Organisational Strategic Manage-ment, Service Planning and Delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.

Advanced computer simulation of the milling process

Process modelling is an integral part of any process industry. Several sugar factory models have been developed over the years to simulate the unit operations. An enhanced and comprehensive milling process simulation model has been developed to analyse the performance of the milling train and to assess the impact of changes and advanced control options for improved operational efficiency. The developed model is incorporated in a proprietary software package ‘SysCAD’. As an example, the milling process model has been used to predict a significant loss of extraction by returning the cush from the juice screen before #3 mill instead of before #2 mill as is more commonly done. Further work is being undertaken to more accurately model extraction processes in a milling train, to examine extraction issues dynamically and to integrate the model into a whole factory model.

Exploring location-dependency in process modeling

Purpose – Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling. Design/methodology/approach – This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases. Findings – This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes. Research limitations/implications – The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies. Originality/value – As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

Detecting approximate clones in business process model repositories

Empirical evidence shows that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication arises for example when the repository covers multiple variants of the same processes or due to copy-pasting. Previous work has addressed the problem of efficiently retrieving exact clones that can be refactored into shared subprocess models. This article studies the broader problem of approximate clone detection in process models. The article proposes techniques for detecting clusters of approximate clones based on two well-known clustering algorithms: DBSCAN and Hi- erarchical Agglomerative Clustering (HAC). The article also defines a measure of standardizability of an approximate clone cluster, meaning the potential benefit of replacing the approximate clones with a single standardized subprocess. Experiments show that both techniques, in conjunction with the proposed standardizability measure, accurately retrieve clusters of approximate clones that originate from copy-pasting followed by independent modifications to the copied fragments. Additional experiments show that both techniques produce clusters that match those produced by human subjects and that are perceived to be standardizable.

Critical linguistics in the early years : exploring functions of language through sophisticated picture books and process drama strategies

In this chapter we describe a critical fairytales unit taught to 4.5 to 5.5 year olds in a context of intensifying pressure to raise literacy achievement. The unit was infused with lessons on reinterpreted fairytales followed by process drama activities built around a sophisticated picture book, Beware of the Bears (MacDonald, 2004). The latter entailed a text analytic approach to critical literacy derived from systemic functional linguistics (Halliday, 1978; Halliday & Matthiessen, 2004). This approach provides a way of analysing how words and discourse are used to represent the world in a particular way and shape reader relations with the author in a particular field (Janks, 2010).

Wood density : a tool to find complementary species for the design of mixed species plantations

The successful establishment and growth of mixed-species forest plantations requires that complementary or facilitatory species be identified. This can be difficult in many tropical areas because the growth characteristics of endemic species are often unknown, particularly when grown at potentially higher densities in plantations than in natural forests. Here, we investigate whether wood density is a useful and readily accessible trait for choosing complementary species for mixed species plantations. Wood density represents the carbon investment per unit volume of stem with a trade-off generally found between fast (low wood density) and slow (high wood density) growing species. To do this, we use data collected from 18 highly diverse mixed species plantations (4–23 mostly native species) aged from 6 to 11 years at the time of data collection located on Leyte Island, Philippines. We found significant negative correlations between wood densities and the height of the most abundant species, as well as with measures of overall stand growth and tree diameter size distribution. Not only do species with denser woods have slower growth rates, but also mixed-species plantations with higher average wood density and higher stem density were also less productive, at least in these young plantations. Similarly, stands with a high diversity in wood densities were less productive. There is growing interest in making greater use of native multi-species mixtures in smallholder and community planting programs in the tropics, and our results show databases of wood density values may help improve their design. In the early development stages of plantations, canopy closure and rapid height growth are usually key silvicultural targets, and wood density values can predict the rapid height development of species. If plantations are being grown for the livelihood of small landholders then the best target is to choose some species with different wood densities. This allows an early harvest of low-wood density species for early income, and will also reduce competition for slower growing trees with higher wood densities for later income generation.