Dzuraidah Abdul Wahab

A framework for organisational change management in lean manufacturing implementation

Lean manufacturing system has been widely applied in manufacturing companies worldwide. However, the low success rate of lean transformations in many countries has given a cause for concern. Much of the literature had pointed out that the main reason is due to the failure in managing the change process during a lean manufacturing transformation. This paper presents a thorough literature review for lean manufacturing approach in the context of organisational change management. Finally, the authors have proposed an organisational change framework for lean manufacturing implementation that would serve as the basis for further empirical research and validation. The framework will further expand the body of knowledge by linking organisational change management with the transition to implementing a lean manufacturing system.

Modelling of palm oil production using fuzzy expert system

The production of crude palm oil and palm kernel is a complex problem due to the influence of processing variables and environmental factors. These processing variables influence the amount of crude palm oil and palm kernel losses during processing. Instead of mathematical model, fuzzy logic approach provides a simpler and easier mechanism to describe the relationships between the processing variables and the amount of crude palm oil and palm kernel losses. In this study, four fuzzy expert system models were developed for each palm oil processing station. An approximation of centre of gravity method for defuzzification is also proposed to enable the development of the model using Microsoft^(R)Excel. For comparison purpose, the models were also developed using MATLAB^(R). Results obtained from the Excel model are found to be very close to the results from MATLAB.

Support vector machines for automated classification of plastic bottles

Many recycling activities adopt manual sorting for plastic recycling that relies on plant personnel who visually identify and pick plastic bottles as they travel along the conveyor belt. These bottles are then sorted into the respective containers. Manual sorting may not be a suitable option for recycling facilities of high throughput. It has also been noted that the high turnover among sorting line workers had caused difficulties in achieving consistency in the plastic separation process. As a result, an intelligent system for automated sorting is greatly needed to replace manual sorting system. The core components of machine vision for this intelligent sorting system is the image recognition and classification.[3]Therefore, in this work, an automated classification of plastic bottles based on the extraction of best feature vectors to represent the type of plastic bottles is performed using the morphological based approach. Morphological operations are used to describe the structure or form of an image. By using the two-dimensional description of plastic bottle silhouettes, edge detection of the object silhouette is performed followed by the erosion process. This procedure can be considered as two stages; a) a feature vector is extracted from the analysis of morphological operation and structure element used and b) a classification technique is applied to that input vector in order to provide a meaningful categorization of the data content. In this study, Support Vector Machines (SVM) was employed merely to classify the image of two groups of plastic bottles namely polyethylene-terephthalate (PET) and non-PET. Additionally, for detailed classification task, the pattern of decision boundary for classification of extracted feature vectors based on morphological approach is also illustrated. Furthermore, the optimal features for input to SVM classifier is identified. The initial results indicate that the performance of the SVM in terms of classification accuracy is more than 90%.

Plastic bottle shape classification using partial erosion-based approach

In this paper, a work on representing plastic bottle shape using erosion based approach for an automated classification is reported. Morphological operations are used to describe the structure or form of an image. By using the two-dimensional description of plastic bottle silhouettes, edge detection of the object silhouette is performed followed by the erosion process. This work will compare two versions of erosion which are regular erosion, the Matlab function imerode and the improved version of erosion which is called partial erosion. Normalization procedure in which the sum pixel value after erosion is divided by the sum pixel of the whole silhouette is done. The normalized values are grouped into histograms of 9 bins of sum pixel value(9HbSPV), find its maximum number to form as a feature set and is then used as inputs to train a neural network for plastic bottle shape classification. Results obtained showed that the proposed feature extraction method can be applied to discriminate plastic bottles according to shape, either slim or broad bottles, efficiently.

CSFs for pre-development implementation of new product development in small and medium-sized enterprises

Success in the pre-development process is important for every organization in order to compete with competitors. In order to survive, organizations need to introduce new products in the marketplace drastically. In view of that, understanding critical success factors (CSFs) that contribute to successfully implementing pre-development is becoming more important. However, most of the past studies were conducted in large organizations; very little has been done in small and medium-size enterprises (SMEs). SMEs have certain limitations in terms of their financial, human, and technical resources that could hinder their progress towards implementing the pre-development. This paper reviews and analyses CSFs developed by previous authors in order to propose a set of CSFs, which were thought to be critical for SMEs. Besides, pre-testing with pre-development experts and SMEs practitioners, the questionnaire was also validated through a pilot study with fifty five SMEs. The questionnaire was designed comprising three compulsory activities of pre-development and CSFs for successful pre-development implementation. The final form of the questionnaire consists of twenty five items of pre-development activities within four constructs, and thirty six items of CSFs within nine constructs. Through systematic identification and validation, it is hoped that the set of CSFs could be used as guides for SMEs to implement the pre-development process successfully.

An efficient segmentation technique for known touching objects using a genetic algorithm approach

This paper presents a genetic algorithm (GA) based segmentation technique that can separate two touching objects intended for an automatic recognition of plastic bottles moving on a conveyor belt. The proposed method is based on the possibility to separate the two objects by means of a straight line, whose position is determined by a GA. Extensive testing shows that the proposed method is fast and yields high success rate of correct segmentation with only a limited number of both chromosomes and iterations.

The use of spreadsheet and queuing network model to optimize capacity utilization in product development

Modeling of a manufacturing system enables one to identify the effects of key design parameters on the system performance and as a result make correct decision. This paper proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates a few parameters such as utilization, cycle time, throughput, and batch size. The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far below the limit value 32%.

An application of failure mode and effect analysis to cylinder head during dismantle of remanufacturing process: a case study

While the concept of remanufacturing is gaining in popularity, in practice the remanufacturing industry in Malaysia is still in its nascent stage, with approximately 32 fields in various industries claiming to be involved in the process. This is an indication for Malaysia to further develop the industry as competing developed countries already view remanufacturing as a huge business opportunity. The aim of this study is to identify and minimize the frequent failures occurring during the dismantling process. Ishikawa diagram is used to identify all possible causes of failures while the Failure Mode and Effect Analysis (FMEA) with two Risk Priority Number (RPNs), identifies the most significant failures. The case study is performed in an automotive industry as well as in a contract remanufacturing environment in Malaysia, specifically pertaining to the dismantling of cylinder heads. The work outcome of this project is expected to be the enhancement of the robustness of DfRem investigations among researchers in real life applications and to provide better solution to a wider variety of industry sectors in a developing country like Malaysia.

Current Situation in Cleaning Process of Remanufacturing in Malaysia: A Case Study

Remanufacturing process among industries is relatively new in Malaysia. In USA, Europe, Japan, China and India, remanufacturing is already viewed as a huge business opportunity that significantly stimulates growth in Gross Domestic Product (GDP) and employment. The aim of this paper is to expose all possible causes of failures using the Ishikawa diagram and identify the most significant failures using Failure Mode and Effect Analysis (FMEA) with two Risk Priority Number (RPNs). The cleaning process is both time-consuming as well as the most costly of the entire remanufacturing processes. The case study is performed in an automotive contract remanufacturing environment in Malaysia, specifically the remanufacturing of cylinder heads. This work outcome explores the current situation pertaining to the cleaning process in a real world situation, and attempts to promote among researchers green ideas that will bring Malaysias remanufacturing on par with that of other developed countries.

Development of 2D Image Capture Method Software for Recognizing Drivers’ Postural Angles

Drivers posture is one of the critical factors that should be investigated closely and thoroughly in the design and development of car drivers seat. A car driver controls the vehicle movements; therefore, his/her safety and comfort is important to avoid any road injury or unfortunate accident. The two main objectives of this study are to develop2D software for capturingimages of drivers postural angles and to collect comfortable drivers postural angles from the participants involved in the study, while they are driving the cars. To achieve this, an experiment was conducted by using this software for collectingcar drivers postural angles. Forty five Malaysian citizens took part in the data collection process. From the study, a 2D image capture method software for capturing driver postural angles were developed. Finally, a range of comfortable postural angles for Malaysian car drivers were proposed based on the participants perception with respect to safety and comfort.