How could construction supply chain benefit from RFID/GPS integration: a knowledge management perspective

Construction materials and equipment are essential building blocks of every construction project and may account for 50-60 per cent of the total cost of construction. The rate of their utilization, on the other hand, is the element that most directly relates to a project progress. A growing concern in the industry that inadequate efficiency hinders its success could thus be accommodated by turning construction into a logistic process. Although mostly limited, recent attempts and studies show that Radio Frequency IDentification (RFID) applications have significant potentials in construction. However, the aim of this research is to show that the technology itself should not only be used for automation and tracking to overcome the supply chain complexity but also as a tool to generate, record and exchange process-related knowledge among the supply chain stakeholders. This would enable all involved parties to identify and understand consequences of any forthcoming difficulties and react accordingly before they cause major disruptions in the construction process. In order to achieve this aim the study focuses on a number of methods. First of all it develops a generic understanding of how RFID technology has been used in logistic processes in industrial supply chain management. Secondly, it investigates recent applications of RFID as an information and communication technology support facility in construction logistics for the management of construction supply chain. Based on these the study develops an improved concept of a construction logistics architecture that explicitly relies on integrating RFID with the Global Positioning System (GPS). The developed conceptual model architecture shows that categorisation provided through RFID and traceability as a result of RFID/GPS integration could be used as a tool to identify, record and share potential problems and thus vastly improve knowledge management processes within the entire supply chain. The findings thus clearly show a need for future research in this area.

Application of logistic regression for fault analysis in an industrial printing process

A statistical technique for fault analysis in industrial printing is reported. The method specifically deals with binary data, for which the results of the production process fall into two categories, rejected or accepted. The method is referred to as logistic regression, and is capable of predicting future fault occurrences by the analysis of current measurements from machine parts sensors. Individual analysis of each type of fault can determine which parts of the plant have a significant influence on the occurrence of such faults; it is also possible to infer which measurable process parameters have no significant influence on the generation of these faults. Information derived from the analysis can be helpful in the operator's interpretation of the current state of the plant. Appropriate actions may then be taken to prevent potential faults from occurring. The algorithm is being implemented as part of an applied self-learning expert system.