International Conference on Nutrition & Food Science (ICNFS 2010) Paris, France 28-30 Julai 2010

Abslract-The proximate composition, physical traits and sensory properties of beef and chicken patties incorporated with various level of dried cornsilk. (MaydiJ stigma) were studied. The beef and ci:J,icken patties were formulated with either 2o/., 4% or 6% of cornsitk. Both cooked beef and chicken patties incorporated with 6% comsilk recorded the highest protein concenttation at 23.3% and 28.42o/o, respectively. Both cooked beef and chicken patties containing 6o/. cornsilk siiruficantly recorded the lowest coDCenlrati.on of fat at ll.4% and 14.60%, respectively. Beef and chicken patties formulated with 6% cornsilk recorded the highest cooking yieJd at 80.13% and 83.03o/. compam:l to other treatments. The inclusion of cornsilk did not change the sensory properties and consumer acceptability of comsilk-ba.sed beef and chicken patties. Cornsilk fibre bali been effective in improving . cooking yield, moisture and fat retention of beef and chicken pattie

Ultrasonic assisted machining

A commercially available DMG MORI ULTRASONIC 65 monoBLOCK machining centre was installed in WMG in 2013 and has been primarily used to machine aerospace grade materials such as carbon fibre reinforced plastic (CFRP) and titanium alloy Ti 6Al-4V (individually and stacked) and 2000 / 6000 series aluminium alloys. Rather than discuss a single set of experimental work in detail, this paper discusses some of the issues that have been encountered when applying the technique of ultrasonic assisted machining (UAM) and some of the effects that have been observed using examples from the research conducted so far to illustrate some of the more important findings

A Methodological Approach to Knowledge-Based Engineering Systems for Manufacturing

A survey of implementations of the knowledge-based engineering approach in different technological sectors is presented. The main objectives and techniques of examined applications are pointed out to illustrate the trends and peculiarities for a number of manufacturing field. Existing methods for the development of these engineering systems are then examined in order to identify critical aspects when applied to manufacturing. A new methodological approach is proposed to overcome some specific limitations that emerged from the above-mentioned survey. The aim is to provide an innovative method for the implementation of knowledge-based engineering applications in the field of industrial production. As a starting point, the field of application of the system is defined using a spatial representation. The conceptual design phase is carried out with the aid of a matrix structure containing the most relevant elements of the system and their relations. In particular, objectives, descriptors, inputs and actions are defined and qualified using categorical attributes. The proposed method is then applied to three case studies with different locations in the applicability space. All the relevant elements of the detailed implementation of these systems are described. The relations with assumptions made during the design are highlighted to validate the effectiveness of the proposed method. The adoption of case studies with notably different applications also reveals the versatility in the application of the method

A Monte-Carlo approach to tool selection for sheet metal punching and nibbling

Selecting the best set of tools to produce certain geometrical shapes/features in sheet metal punching is one of the problems that has a great effect on product development time, cost and achieved quality. The trend nowadays is, where at all possible, to limit design to the use of standard tools. Such an option makes the problem of selecting the appropriate set of tools even more complex, especially when considering that sheet metal features can have a wide range of complex shapes. Another dimension of complexity is limited tool rack capacity. Thus, an inappropriate tool selection strategy will lead to punching inefficiency and may require frequent stopping of the machine and replacing the required tools, which is a rather expensive and time consuming exercise. This work demonstrates that the problem of selecting the best set of tools is actually a process of searching an explosive decision tree. The difficulty in searching such types of decision trees is that intermediate decisions do not necessarily reflect the total cost implication of carrying out such a decision. A new approach to solve such a complex optimisation problem using the Monte Carlo Simulation Methods has been introduced in this thesis. The aim of the present work was to establish the use of Monte Carlo methods as an "assumptions or rule free" baseline or benchmark for the assessment of search strategies. A number of case studies are given, where the feasibility of Monte Carlo Simulation Methods as an efficient and viable method to optimise such a complex optimisation problem is demonstrated. The use of a Monte Carlo approach for selecting the best set of punching tools, showed an interesting point, that is, the effect of dominant "one-to-one" feature/tool matches on the efficiency of the search. This naturally led on to the need of a search methodology that will be more efficient than the application of the Monte Carlo method alone. This thesis presents some interesting speculations for a hybrid approach to tool selection to achieve a better solution than the use of the Monte Carlo method alone to achieve the optimum solution in a shorter time

Development of a network-integrated feature-driven engineering environment

Ph.DDOCTOR OF PHILOSOPH

Fixtureless automated incremental sheet metal forming

Die-based forming is a technology used by many industries to form metal panels. However, this method of forming lacks flexibility and cost effectiveness. In such cases, manual panel beating is typically undertaken for incremental forming of metal panels. Manual panel forming is a highly skilled operation with very little documentation and is disappearing due to non-observance and a lack of interest. Confederation of British Metal forming (CBM) and Institution of Sheet Metal Engineering (ISME) have realised the need for capturing and understanding manual skills used by panel beaters to preserve the knowledge. At the same time, industries seek for alternative panel forming solutions to produce high quality and cost-effective parts at low volume and reduce the repetitive, yet adaptive parts of the panel forming process to free up skilled workers to concentrate on the forming activities that are more difficult to automate. Incremental forming technologies, currently in practice, lack adaptability as they require substantial fixtures and dedicated tools. In this research a new proof-of-concept fixtureless automated sheet metal forming approach was developed on the basis of human skills captured from panel beaters. The proposed novel approach, named Mechatroforming®, consists of integrated mechanisms to form simple sheet metal parts by manipulating the workpiece using a robotic arm under a repetitive hammering tool. Predictive motion planning based on FEA was analysed and the manual forming skills were captured using a motion capture system. This facilitated the coordinated hammering and motion of the part to produce the intended shape accurately. A 3D measurement system with a vertical resolution of 50μm was also deployed to monitor the formation of the parts and make corrections to the forming path if needed. Therefore, the developed mechatronic system is highly adjustable by robotic motion and was closed loop via the 3D measurement system. The developed automated system has been tested rigorously, initially for bowl shape parts to prove the principle. The developed system which is 98% repeatable for depth and diameter, is able to produce targeted bowl shape parts with ±1% dimensional accuracy, high surface quality, and uniform material thickness of 0.95mm when tested with aluminium. It is envisaged that by further research, the proposed approach can be extended to form irregular and more complicated shapes that are highly in demand in various industries

Robots in machining

Robotic machining centers offer diverse advantages: large operation reach with large reorientation capability, and a low cost, to name a few. Many challenges have slowed down the adoption or sometimes inhibited the use of robots for machining tasks. This paper deals with the current usage and status of robots in machining, as well as the necessary modelling and identification for enabling optimization, process planning and process control. Recent research addressing deburring, milling, incremental forming, polishing or thin wall machining is presented. We discuss various processes in which robots need to deal with significant process forces while fulfilling their machining task