Computer experiment – a case study for modelling and simulation of manufacturing systems

Deterministic computer simulation of physical experiments is now a common technique in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments lead to the study of computer experiments, which are used to investigate many scientific phenomena. A computer experiment consists of a number of runs of the computer code with different input choices. The Design and Analysis of Computer Experiments is a rapidly growing technique in statistical experimental design. This paper aims to discuss some practical issues when designing a computer simulation and/or experiments for manufacturing systems. A case study approach is reviewed and presented.

The architecture of children’s use of language and tools when problem solving collaboratively with robotics

This paper demonstrates, following Vygotsky, that language and tool use has a critical role in the collaborative problem-solving behaviour of school-age children. It reports original ethnographic classroom research examining the convergence of speech and practical activity in children’s collaborative problem solving with robotics programming tasks. The researchers analysed children’s interactions during a series of problem solving experiments in which Lego Mindstorms toolsets were used by teachers to create robotics design challenges among 24 students in a Year 4 Australian classroom (students aged 8.5–9.5 years). The design challenges were incrementally difficult, beginning with basic programming of straight line movement, and progressing to more complex challenges involving programming of the robots to raise Lego figures from conduit pipes using robots as pulleys with string and recycled materials. Data collection involved micro-genetic analysis of students’ speech interactions with tools, peers, and other experts, teacher interviews, and student focus group data. Coding the repeated patterns in the transcripts, the authors outline the structure of the children’s social speech in joint problem solving, demonstrating the patterns of speech and interaction that play an important role in the socialisation of the school-age child’s practical intellect.

A systematic approach for selecting lean strategies and assessing leanness in manufacturing organizations

Lean strategies have been developed to eliminate or reduce manufacturing waste and thus improve operational efficiency in manufacturing processes. However, implementing lean strategies requires a large amount of resources and, in practice, manufacturers encounter difficulties in selecting appropriate lean strategies within their resource constraints. There is currently no systematic methodology available for selecting appropriate lean strategies within a manufacturer's resource constraints. In the lean transformation process, it is also critical to measure the current and desired leanness levels in order to clearly evaluate lean implementation efforts. Despite the fact that many lean strategies are utilized to reduce or eliminate manufacturing waste, little effort has been directed towards properly assessing the leanness of manufacturing organizations. In practice, a single or specific group of metrics (either qualitative or quantitative) will only partially measure the overall leanness. Existing leanness assessment methodologies do not offer a comprehensive evaluation method, integrating both quantitative and qualitative lean measures into a single quantitative value for measuring the overall leanness of an organization. This research aims to develop mathematical models and a systematic methodology for selecting appropriate lean strategies and evaluating the leanness levels in manufacturing organizations. Mathematical models were formulated and a methodology was developed for selecting appropriate lean strategies within manufacturers' limited amount of available resources to reduce their identified wastes. A leanness assessment model was developed by using the fuzzy concept to assess the leanness level and to recommend an optimum leanness value for a manufacturing organization. In the proposed leanness assessment model, both quantitative and qualitative input factors have been taken into account. Based on program developed in MATLAB and C#, a decision support tool (DST) was developed for decision makers to select lean strategies and evaluate the leanness value based on the proposed models and methodology hence sustain the lean implementation efforts. A case study was conducted to demonstrate the effectiveness of these proposed models and methodology. Case study results suggested that out of 10 wastes identified, the case organization (ABC Limited) is able to improve a maximum of six wastes from the selected workstation within their resource limitations. The selected wastes are: unnecessary motion, setup time, unnecessary transportation, inappropriate processing, work in process and raw material inventory and suggested lean strategies are: 5S, Just-In-Time, Kanban System, the Visual Management System (VMS), Cellular Manufacturing, Standard Work Process using method-time measurement (MTM), and Single Minute Exchange of Die (SMED). From the suggested lean strategies, the impact of 5S was demonstrated by measuring the leanness level of two different situations in ABC. After that, MTM was suggested as a standard work process for further improvement of the current leanness value. The initial status of the organization showed a leanness value of 0.12. By applying 5S, the leanness level significantly improved to reach 0.19 and the simulation of MTM as a standard work method shows the leanness value could be improved to 0.31. The optimum leanness value of ABC was calculated to be 0.64. These leanness values provided a quantitative indication of the impacts of improvement initiatives in terms of the overall leanness level to the case organization. Sensitivity analsysis and a t-test were also performed to validate the model proposed. This research advances the current knowledge base by developing mathematical models and methodologies to overcome lean strategy selection and leanness assessment problems. By selecting appropriate lean strategies, a manufacturer can better prioritize implementation efforts and resources to maximize the benefits of implementing lean strategies in their organization. The leanness index is used to evaluate an organization's current (before lean implementation) leanness state against the state after lean implementation and to establish benchmarking (the optimum leanness state). Hence, this research provides a continuous improvement tool for a lean manufacturing organization.

Unpacking the opportunities for change within a family owned manufacturing sme : a design led innovation case study

This thesis explored how an Australian, family owned, manufacturing firm responded to a design led innovation approach as conducted by the action researcher. Specifically, it investigated the barriers and opportunities that arose within the firm when trying to affect change to drive innovation. In doing so, key opportunities were identified that could help the firm to integrate a design led approach and remain competitive within an increasingly accessible global marketplace.

An activity and resource advisory system for manufacturing process chains selection at the early stage of product development

Designers need to consider both the functional and production process requirements at the early stage of product development. A variety of the research works found in the literature has been proposed to assist designers in selecting the most viable manufacturing process chain. However, they do not provide any assistance for designers to evaluate the processes according to the particular circumstances of their company. This paper describes a framework of an Activity and Resource Advisory System (ARAS) that generates advice about the required activities and the possible resources for various manufacturing process chains. The system provides more insight, more flexibility, and a more holistic and suitable approach for designers to evaluate and then select the most viable manufacturing process chain at the early stage of product development.

Efficiency and productivity of Singapore's manufacturing sector 2001-2010 : an analysis using bootstrapped truncated approach

This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity (TFP) change and Simar and Wilson’s (2007) bootstrapped truncated regression approach which first derives bias-corrected efficiency estimates before being regressed against explanatory variables to help quantify sources of inefficiencies. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Sources of efficiency were attributed to quality of worker and flexible work arrangements while the use of foreign workers lowered efficiency.

Condition monitoring and operational decision making in semiconductor manufacturing

Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.

A time-based quantitative approach for selecting lean strategies for manufacturing organisations

Lean strategies have been developed to eliminate or reduce waste and thus improve operational efficiency in a manufacturing environment. However, in practice, manufacturers encounter difficulties to select appropriate lean strategies within their resource constraints and to quantitatively evaluate the perceived value of manufacturing waste reduction. This paper presents a methodology developed to quantitatively evaluate the contribution of lean strategies selected to reduce manufacturing wastes within the manufacturers’ resource (time) constraints. A mathematical model has been developed for evaluating the perceived value of lean strategies to manufacturing waste reduction and a step-by-step methodology is provided for selecting appropriate lean strategies to improve the manufacturing performance within their resource constraints. A computer program is developed in MATLAB for finding the optimum solution. With the help of a case study, the proposed methodology and developed model has been validated. A ‘lean strategy-wastes’ correlation matrix has been proposed to establish the relationship between the manufacturing wastes and lean strategies. Using the correlation matrix and applying the proposed methodology and developed mathematical model, authors came out with optimised perceived value of reduction of a manufacturer's wastes by implementing appropriate lean strategies within a manufacturer's resources constraints. Results also demonstrate that the perceived value of reduction of manufacturing wastes can significantly be changed based on policies and product strategy taken by a manufacturer. The proposed methodology can also be used in dynamic situations by changing the input in the programme developed in MATLAB. By identifying appropriate lean strategies for specific manufacturing wastes, a manufacturer can better prioritise implementation efforts and resources to maximise the success of implementing lean strategies in their organisation.

Application of lean production to reducing operational waste in a tile manufacturing process

Roofing tile manufacturing is a mass production process with high operational and inventory wastes and costs. Due to huge operational costs, excessive inventory and wastes, and quality problems, roofing tile manufacturers are trying to implement lean manufacturing practice in their operations in order to remain competitive in an ncreasingly competitive global market. The aim of this research is to evaluate the possibility of reducing the operational and inventory costs of the tile manufacturing process through waste minimization. This paper analyses the current waste situation in a tile manufacturing process and develops current and future value stream mapping for such a process with a view to implementing lean principles in manufacturing. The focus of the approach is on cost reduction by eliminating non-value-added activities.

A methodology for effective implementation of lean strategies and its performance evaluation in manufacturing organizations

Purpose – The purpose of this paper is to develop an effective methodology for implementing lean manufacturing strategies and a leanness evaluation metric using continuous performance measurement (CPM). Design/methodology/approach – Based on five lean principles, a systematic lean implementation methodology for manufacturing organizations has been proposed. A simplified leanness evaluation metric consisting of both efficiency and effectiveness attributes of manufacturing performance has been developed for continuous evaluation of lean implementation. A case study to validate the proposed methodology has been conducted and proposed CPM metric has been used to assess the manufacturing leanness. Findings – Proposed methodology is able to systematically identify manufacturing wastes, select appropriate lean tools, identify relevant performance indicators, achieve significant performance improvement and establish lean culture in the organization. Continuous performance measurement matrices in terms of efficiency and effectiveness are proved to be appropriate methods for continuous evaluation of lean performance. Research limitations/implications – Effectiveness of the method developed has been demonstrated by applying it in a real life assembly process. However, more tests/applications will be necessary to generalize the findings. Practical implications – Results show that applying the methods developed, managers can successfully identify and remove manufacturing wastes from their production processes. By improving process efficiency, they can optimize their resource allocations. Manufacturers now have a validated step by step methodology for successfully implementing lean strategies. Originality/value – According to the authors’ best knowledge, this is the first known study that proposed a systematic lean implementation methodology based on lean principles and continuous improvement techniques. Evaluation of performance improvement by lean strategies is a critical issue. This study develops a simplified leanness evaluation metric considering both efficiency and effectiveness attributes and integrates it with the lean implementation methodology.

Low cost localisation for agricultural robotics

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

Laser-camera data discrepancies and reliable perception in outdoor robotics

This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.

Creating synergy in teacher education through robotics-based STEM activities

Robotics has created opportunities for educators to teach concepts across Science, Technology, Engineering, and Mathematics (STEM). This is one of the reasons robotics is becoming increasingly common in primary and secondary classrooms in Australia. To enable pre-service teachers to design engaging STEM activities that incorporate these technologies, robotics is part of the teaching program in the primary education degree at Queensland University of Technology (QUT). A number of pre-service teachers also choose to extend their abilities by implementing robotics activities on field studies, in schools on a voluntary basis, and in outreach activities such as the Robotics@QUT project. The Robotics@QUT project is a support network developed to build professional knowledge and capacity of classroom teachers in schools from a low SES area, engaging in robotics-based STEM activities. Professional Development (PD) workshops are provided to teachers in order to build their knowledge and confidence in implementing robotics activities in their classrooms, loan kits are provided, and pre-service teacher visits arranged to provide the teachers with on-going support. A key feature of the project is the partnerships developed between the teachers and the pre-service teachers involved in the project. The purpose of this study was to ascertain how the teachers in the project perceived the value of the PD workshops and the pre-service teachers’ involvement and what the benefits of the involvement in the project were for the pre-service teachers. Seventeen teachers completed a five-point (1-5) likert scale questionnaire regarding their involvement in the Robotics@QUT project. Teachers’ responses on the value of the project and the pre-service teacher support highlighted the benefits of the partnerships formed and provided insights into the value of the support provided by the pre-service teachers. This paper also describes one pre-service teacher’s experience with the project and the perceived benefits from being involved.

A collaborative robotics engagement project

This paper reports on an evaluation of a collaborative robotics engagement project involving teachers from local schools and an academic from Queensland University of Technology (QUT). Engaged community projects are aimed at building stronger relationships between universities and their local communities (Sandman, Williams & Abrams, 2009). This partnership leads to mutually beneficial outcomes, builds community capacity, and can focus on aspirations and access to higher education for school students (Scull & Cuthill, 2010). The Robotics@QUT project aimed to build a partnership between local teachers and the university in order to provide students from a low SES area opportunity to engage in robotics-based Science, Technology, Engineering, and Mathematics (STEM) activities. Students from low SES regions are underrepresented at university and less likely to pursue studies in these fields (Bradley, Noonan, Nugent, & Scales, 2008). Having teachers who provide engaging STEM activities is an important motivating factor for students to enjoy STEM and do well in STEM subjects (Tytler, Osborne Williams Tytler & Clark, 2008).