Predictive Monitoring of Business Processes

Modern information systems that support complex business processes generally maintain significant amounts of process execution data, particularly records of events corresponding to the execution of activities (event logs). In this paper, we present an approach to analyze such event logs in order to predictively monitor business goals during business process execution. At any point during an execution of a process, the user can define business goals in the form of linear temporal logic rules. When an activity is being executed, the framework identifies input data values that are more (or less) likely to lead to the achievement of each business goal. Unlike reactive compliance monitoring approaches that detect violations only after they have occurred, our predictive monitoring approach provides early advice so that users can steer ongoing process executions towards the achievement of business goals. In other words, violations are predicted (and potentially prevented) rather than merely detected. The approach has been implemented in the ProM process mining toolset and validated on a real-life log pertaining to the treatment of cancer patients in a large hospital

Specification-Driven Predictive Business Process Monitoring

Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs). In practice, different business domains might require different kinds of predictions. Hence, it is important to have a means for properly specifying the desired prediction tasks, and a mechanism to deal with these various prediction tasks. Although there have been many studies in this area, they mostly focus on a specific prediction task. This work introduces a language for specifying the desired prediction tasks, and this language allows us to express various kinds of prediction tasks. This work also presents a mechanism for automatically creating the corresponding prediction model based on the given specification. Differently from previous studies, instead of focusing on a particular prediction task, we present an approach to deal with various prediction tasks based on the given specification of the desired prediction tasks. We also provide an implementation of the approach which is used to conduct experiments using real-life event logs.Comment: This article significantly extends the previous work in https://doi.org/10.1007/978-3-319-91704-7_7 which has a technical report in arXiv:1804.00617. This article and the previous work have a coauthor in commo

Towards cleaner production: a roadmap for predicting product end-of-life costs at early design concept

The primary objective of the research was to investigate how disposal costs were being incurred in the domain of defence electronic systems by the Original Equipment Manufacturer (OEM) and subsequently to ascertain a novel approach to prediction of their end-of-life (EOL) costs. It is intended that the OEM could utilise this method as part of a full lifecycle cost analysis at the conceptual design stage. The cost model would also serve as a useful guide to aid decision making at the conceptual design stage, so that it may lead to the design of a more sustainable product in terms of recycling, refurbishment or remanufacture with the consideration of financial impact. The novelty of this research is that it identifies the significance of disposal costs from the viewpoint of the OEM and provides a generic basis for evaluation of all the major EOL defence electronic systems. A roadmap has been proposed and developed to facilitate the prediction of disposal costs and this will be used to determine a satisfactory solution of whether the EOL parts of a defence electronic system are viable to be remanufactured, refurbished or recycled from an early stage of a design concept. A selected defence electronic system is used as a case study. Based on the findings, the proposed method offers a manageable and realistic solution so that the OEM can estimate the cost of potential EOL recovery processes at the concept design stag

Development of a conceptual framework for integrated analysis and assessment of agricultural systems in SEAMLESS-IF

Production Economics,

Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given

Correlations Between Management Behaviors and Financial Indicators with FDA Compliance Leading to Medicine Shortages

In the first 3 years of the Obama Administration, 2009-2011, the number of warning letters issued to pharmaceutical firms for manufacturing and quality issues increased by 81% to 49 letters. Only 9 letters were issued in the last 3 years of the George W. Bush Administration. Shortfalls in compliance and product quality led to medicine shortages that affected patients\u27 treatment and health. This quantitative study sought to learn to what extent, if any, the independent variables, management behaviors and financial indicators at pharmaceutical firms in the United States, correlated with, or predicted, the dependent variable, compliance with the FDA regulations. FDA\u27s enforcement actions on the firms were the treatment event. A shift in the relationship between the variables occurred after the FDA interventions, which highlighted a new level of compliance. Of the 1144 SurveyMonkey invitations sent to the members of the International Society of Pharmaceutical Engineers, only 21 completed the survey\u27s 133 questions. Three research questions were addressed using correlations and linear regressions. The theory of planned behavior was applied to correlate behavioral constructs with the compliance of the firms leading to the rejection of the null hypothesis. By establishing an inverse relation between financial indicators and the firms\u27 level of compliance, the study offers awareness and insight to senior leaders regarding their behaviors and the decision-making process. Enhancing managers\u27 decision-making processes in light of their beliefs, along with their control over financial indicators, could reinforce the presence of effective quality systems among pharmaceutical manufacturers minimizing medicine shortages

Semantic framework for regulatory compliance support

Regulatory Compliance Management (RCM) is a management process, which an organization implements to conform to regulatory guidelines. Some processes that contribute towards automating RCM are: (i) extraction of meaningful entities from the regulatory text and (ii) mapping regulatory guidelines with organisational processes. These processes help in updating the RCM with changes in regulatory guidelines. The update process is still manual since there are comparatively less research in this direction. The Semantic Web technologies are potential candidates in order to make the update process automatic. There are stand-alone frameworks that use Semantic Web technologies such as Information Extraction, Ontology Population, Similarities and Ontology Mapping. However, integration of these innovative approaches in the semantic compliance management has not been explored yet. Considering these two processes as crucial constituents, the aim of this thesis is to automate the processes of RCM. It proposes a framework called, RegCMantic. The proposed framework is designed and developed in two main phases. The first part of the framework extracts the regulatory entities from regulatory guidelines. The extraction of meaningful entities from the regulatory guidelines helps in relating the regulatory guidelines with organisational processes. The proposed framework identifies the document-components and extracts the entities from the document-components. The framework extracts important regulatory entities using four components: (i) parser, (ii) definition terms, (iii) ontological concepts and (iv) rules. The parsers break down a sentence into useful segments. The extraction is carried out by using the definition terms, ontological concepts and the rules in the segments. The entities extracted are the core-entities such as subject, action and obligation, and the aux-entities such as time, place, purpose, procedure and condition. The second part of the framework relates the regulatory guidelines with organisational processes. The proposed framework uses a mapping algorithm, which considers three types of Abstract 3 entities in the regulatory-domain and two types of entities in the process-domains. In the regulatory-domain, the considered entities are regulation-topic, core-entities and aux-entities. Whereas, in the process-domain, the considered entities are subject and action. Using these entities, it computes aggregation of three types of similarity scores: topic-score, core-score and aux-score. The aggregate similarity score determines whether a regulatory guideline is related to an organisational process. The RegCMantic framework is validated through the development of a prototype system. The prototype system implements a case study, which involves regulatory guidelines governing the Pharmaceutical industries in the UK. The evaluation of the results from the case-study has shown improved accuracy in extraction of the regulatory entities and relating regulatory guidelines with organisational processes. This research has contributed in extracting meaningful entities from regulatory guidelines, which are provided in unstructured text and mapping the regulatory guidelines with organisational processes semantically