Identifying product families using data mining techniques in manufacturing paradigm

Identifying product families has been considered as an effective way to accommodate the increasing product varieties across the diverse market niches. In this paper, we propose a novel framework to identifying product families by using a similarity measure for a common product design data BOM (Bill of Materials) based on data mining techniques such as frequent mining and clus-tering. For calculating the similarity between BOMs, a novel Extended Augmented Adjacency Matrix (EAAM) representation is introduced that consists of information not only of the content and topology but also of the fre-quent structural dependency among the various parts of a product design. These EAAM representations of BOMs are compared to calculate the similarity between products and used as a clustering input to group the product fami-lies. When applied on a real-life manufacturing data, the proposed framework outperforms a current baseline that uses orthogonal Procrustes for grouping product families.

Bill of Joseph Jacobs for baking matzah

Digital image

Bill of Hayman Levy to K. K. S. I.

Digital image

Copy of bill of exchange of Haym Salomon and letter regarding the same

Digital image

Bill of Israel Joel for Israel Israel

Digital image

Copy of 1794 bill of sale of the ship "Farmer"

Digital image

Copy of bill of costs for Lewis Gomes' denization

Digital image

Copy of letter from Jacques Judah Lyons to Sir Moses Montefiore enclosing bill of exchange for Palestinian Jews

Digital image

Non-parametric bill of quantities estimation of concrete road bridges' superstructure: an artificial neural networks approach

Bridge construction responds to the need for environmentally friendly design of motorways and facilitates the passage through sensitive natural areas and the bypassing of urban areas. However, according to numerous research studies, bridge construction presents substantial budget overruns. Therefore, it is necessary early in the planning process for the decision makers to have reliable estimates of the final cost based on previously constructed projects. At the same time, the current European financial crisis reduces the available capital for investments and financial institutions are even less willing to finance transportation infrastructure. Consequently, it is even more necessary today to estimate the budget of high-cost construction projects -such as road bridges- with reasonable accuracy, in order for the state funds to be invested with lower risk and the projects to be designed with the highest possible efficiency. In this paper, a Bill-of-Quantities (BoQ) estimation tool for road bridges is developed in order to support the decisions made at the preliminary planning and design stages of highways. Specifically, a Feed-Forward Artificial Neural Network (ANN) with a hidden layer of 10 neurons is trained to predict the superstructure material quantities (concrete, pre-stressed steel and reinforcing steel) using the width of the deck, the adjusted length of span or cantilever and the type of the bridge as input variables. The training dataset includes actual data from 68 recently constructed concrete motorway bridges in Greece. According to the relevant metrics, the developed model captures very well the complex interrelations in the dataset and demonstrates strong generalisation capability. Furthermore, it outperforms the linear regression models developed for the same dataset. Therefore, the proposed cost estimation model stands as a useful and reliable tool for the construction industry as it enables planners to reach informed decisions for technical and economic planning of concrete bridge projects from their early implementation stages.

Computerised control of cellular manufacturing systems

This thesis reviews the existing manufacturing control techniques and identifies their practical drawbacks when applied in a high variety, low and medium volume environment. It advocates that the significant drawbacks inherent in such systems, could impair their applications under such manufacturing environment. The key weaknesses identified in the system were: capacity insensitive nature of Material Requirements Planning (MRP); the centralised approach to planning and control applied in Manufacturing Resources Planning (MRP IT); the fact that Kanban can only be used in repetitive environments; Optimised Productivity Techniques's (OPT) inability to deal with transient bottlenecks, etc. On the other hand, cellular systems offer advantages in simplifying the control problems of manufacturing and the thesis reviews systems designed for cellular manufacturing including Distributed Manufacturing Resources Planning (DMRP) and Flexible Manufacturing System (FMS) controllers. It advocates that a newly developed cellular manufacturing control methodology, which is fully automatic, capacity sensitive and responsive, has the potential to resolve the core manufacturing control problems discussed above. It's development is envisaged within the framework of a DMRP environment, in which each cell is provided with its own MRP II system and decision making capability. It is a cellular based closed loop control system, which revolves on single level Bill-Of-Materials (BOM) structure and hence provides better linkage between shop level scheduling activities and relevant entries in the MPS. This provides a better prospect of undertaking rapid response to changes in the status of manufacturing resources and incoming enquiries. Moreover, it also permits automatic evaluation of capacity and due date constraints and hence facilitates the automation of MPS within such system. A prototype cellular manufacturing control model, was developed to demonstrate the underlying principles and operational logic of the cellular manufacturing control methodology, based on the above concept. This was shown to offer significant advantages from the prospective of operational planning and control. Results of relevant tests proved that the model is capable of producing reasonable due date and undertake automation of MPS. The overall performance of the model proved satisfactory and acceptable.

The meaning of 'material prejudice'

As dictated by s 213 of the Body Corporate and Community Management Act 1997 (Qld), the seller of a proposed lot is required to provide the buyer with a disclosure statement before the contract is entered into. Where the seller subsequently becomes aware that information contained in the disclosure statement was inaccurate when the contract was entered into or the disclosure statement would not be accurate if now given as a disclosure statement, the seller must, within 14 days, give the buyer a further statement rectifying the inaccuracies in the disclosure statement. Provided the contract has not been settled, where a further statement varies the disclosure statement to such a degree that the buyer would be materially prejudiced if compelled to complete the contract, the buyer may cancel the contract by written notice given to the seller within 14 days, or a longer period as agreed between the parties, after the seller gives the buyer the further statement. The term ‘material prejudice’ was considered by Wilson J in Wilson v Mirvac Queensland Pty Ltd.

Queensland Court of Appeal opines on the meaning of 'material prejudice'

The decision of Wilson J in Wilson v Mirvac Queensland Pty Ltd was the subject of an article in an earlier edition of this journal. At that time, it was foreshadowed that the decision was to be taken on appeal. The decision of the Court of Appeal in Mirvac Queensland Pty Ltd v Wilson is considered in this article.

Numerical modelling and analysis of the blast performance of laminated glass panels and the influence of material parameters

This paper presents a comprehensive numerical procedure to treat the blast response of laminated glass (LG) panels and studies the influence of important material parameters. Post-crack behaviour of the LG panel and the contribution of the interlayer towards blast resistance are treated. Modelling techniques are validated by comparing with existing experimental results. Findings indicate that the tensile strength of glass considerably influences the blast response of LG panels while the interlayer material properties have a major impact on the response under higher blast loads. Initially, glass panes absorb most of the blast energy, but after the glass breaks, interlayer deforms further and absorbs most of the blast energy. LG panels should be designed to fail by tearing of the interlayer rather than failure at the supports to achieve a desired level of protection. From this aspect, material properties of glass, interlayer and sealant joints play important roles, but unfortunately they are not accounted for in the current design standards. The new information generated in this paper will enhance the capabilities of engineers to better design LG panels under blast loads and use better materials to improve the blast response of LG panels.