Overcoming integration challenges in organisations with operational technology

Competitive advantage is traditionally an outcome of leveraging people, processes and technologies. Today organisations have several technologies with disparate information. Information integration may assist organisations to remain competitive. Organisations that have technology which manage or control assets have particular integration challenges compared to organisations with corporate business areas. This is because organisations do not view technology managing infrastructure assets in the same way as managing functions such as finance, retail and human resources. The paper defines a current, asset management based taxonomy for organisations integrating Operational and Information Technology. It identifies a number of challenges, such as the commitment to information integration, organisation-wide governance and architectural approaches as well as the aligning of operational open standards with existing information technology standards. Furthermore it highlights opportunities for further research in the area

Understanding the use of smart mobile technologies for learning in higher education

This paper presents a preliminary exploration of the types of smart mobile technologies higher education students have access to and use to support their learning by comparing cohorts from two Australian universities with quite different profiles, the University of Southern Queensland (USQ) and the University of South Australia (UniSA). These results are briefly compared to those obtained in earlier studies in a broad attempt to identify trends in the use of mobile technologies to support learning over time. The results indicate that levels of smart phone ownership are rising rapidly with a corresponding drop in levels of feature phone ownership. Tablet computers such as iPads have emerged since the earlier studies were completed with high levels of adoption by students. Significantly, students are using these smart mobile devices to support their learning

How Do Students Use Their Mobile Devices to Support Learning? A Case Study from an Australian Regional University

Though universities are eager to leverage the potential of mobile learning to provide learning flexibly, most balk at the cost of providing students with mobile hardware. The practice of ‘bring your own device’ (BYOD) is often mooted as a cost-effective alternative. This paper provides a snapshot of student ownership of mobile devices at a regional Australian university. Our research shows that students do have access to and use a wide range of devices. However, the delivery of learning is challenged when students try to access materials and activities using these devices. Course materials are rarely optimised for use on smartphones, navigating websites and learning management systems becomes a scrolling nightmare, and interacting with other students is often impractical using prescribed systems. Most concerning is that none of the students surveyed were participating in educator-led mobile learning initiatives. The paper concludes with the proposal of some practical, low-cost tactics that educators could potentially employ to begin engaging with mobile learning, leveraging what students already do

OT Modeling: The Enterprise Beyond IT

Enterprises are composed of an enormous number of elements (e.g., organizational units, human resources, production processes, and IT systems) typically classified in the business or the IT domain. However, some crucial elements do not belong in either group: they are directly responsible for producing and delivering the company’s goods and services and include all the elements that support day to day operations. Collectively, these elements have been called operational technologies (OT) and have been conspicuously excluded from enterprise modeling (EM) approaches which traditionally have focused on the business and IT dimensions. Evidence of this is the absence of OT elements in languages and metamodels for EM. This is in line with the historical division between IT and OT in organizations that has led to information silos, independent teams, and disparate tech- nologies that only recently have started to be reconciled. Considering that OT is critical to most productive organi- zations, and the benefits that EM brings to its understand- ing and improvement, it makes sense to expand EM to include OT. For that purpose, this paper proposes an extension to ArchiMate 3.0 which includes crucial OT elements. On top of that, this paper also proposes an approach to further expand ArchiMate to address specific industries where more specific OT elements are required. This is illustrated in the paper with an extension for the Oil and Gas case that was validated with experts belonging to five companies in the sector

Intelligent decision support for maintenance: an overview and future trends

The changing nature of manufacturing, in recent years, is evident in industry’s willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable ‘Human in the loop’ interactions

Classifying data quality problems in asset management

Making sound asset management decisions, such as whether to replace or maintain an ageing underground water pipe, are critical to ensure that organisations maximise the performance of their assets. These decisions are only as good as the data that supports them, and hence many asset management organisations are in desperate need to improve the quality of their data. This chapter reviews the key academic research on data quality (DQ) and Information Quality (IQ) (used interchangeably in this chapter) in asset management, combines this with the current DQ problems faced by asset management organisations in various business sectors, and presents a classification of the most important DQ problems that need to be tackled by asset management organisations. In this research, eleven semi structured interviews were carried out with asset management professionals in a range of business sectors in the UK. The problems described in the academic literature were cross checked against the problems found in industry. In order to support asset management professionals in solving these problems, we categorised them into seven different DQ dimensions, used in the academic literature, so that it is clear how these problems fit within the standard frameworks for assessing and improving data quality. Asset management professionals can therefore now use these frameworks to underpin their DQ improvement initiatives while focussing on the most critical DQ problems

Motivating Public Sector Employees: Evidence from Greece

Purpose: The object of this research is to investigate work motivating factors in the public sector in Greece, as well as to study demographic attributes, placing emphasis on age and gender as determinants of employee motives. Design/methodology/approach: To answer our research questions, a questionnaire was distributed at the beginning of 2015 to a public - sector organization in central Greece. A total of 318 anonymous survey responses were collected and analysed with SPSS. Findings: In the public organization under survey, the leading employee motives are an increase in salaries, opportunities for hierarchical advancement in the organization, as well as the development of personal skills. Moreover, motivational differences are noted among Baby Boomers, Generation X and Generation Y. Research limitations/implications: As the present study has been conducted on a single public organization, awareness should be raised as far as the generalizability of the results providing useful insights for further exploration. Originality/value: Limited research has been conducted in the Greek public sector comparing motives among generations