The impact of gender diversity on performance in services and manufacturing organizations

We present three competing predictions of the organizational gender diversity-performance relationship: a positive linear prediction, a negative linear prediction, and an inverted U-shaped curvilinear prediction. The paper also proposes a moderating effect of industry type (services vs. manufacturing). The predictions were tested using archival quantitative data with a longitudinal design. The results show partial support for the positive linear and inverted U-shaped curvilinear predictions as well as for the proposed moderating effect of industry type. The results help reconcile the inconsistent findings of past research. The findings also show that industry context can strengthen or weaken gender diversity effects.

Service enhanced manufacturing in the building and construction product system

This report examines the involvement of manufacturers in value-adding through service-enhancement of product offerings. This focus has been prompted by:  emphasis in the knowledge-economy literature on the increasing role played by services in economic growth; and  recent analysis which suggests that the most dynamic sector of many economies is an integrated manufacturing-services sector (see Part One of this report). The report initially describes the emergence of an integrated manufacturing-services sector in the context of increasingly knowledge-based economic systems. Part Two reports on the results of a survey of manufacturers in the building and construction product system, investigating their involvement in service provision. Parts Three and Four present two case studies of exemplary manufacturers involved in adding value to their manufacturing operations through services offered on building and construction projects. The report examines manufacturers of materials, products, equipment and machinery used on building and construction projects. The two case study sections of the report, in part, focus on a major project undertaken by each of the manufacturers. This project element of activity is focussed on (as opposed to wholesale or retail supply), because this area of activity involves a broader array of service-enhancement mechanisms and more complex bundling of products and services.

The gender diversity-performance relationship in services and manufacturing organizations

Empirical findings on the link between gender diversity and performance have been inconsistent. This paper presents three competing predictions of the organizational gender diversity-performance relationship: a positive linear prediction derived from the resource-based view of the firm, a negative linear prediction derived from self-categorization and social identity theories, and an inverted U-shaped curvilinear prediction derived from the integration of the resource-based view of the firm with self-categorization and social identity theories. This paper also proposes a moderating effect of industry type (services vs. manufacturing) on the gender diversity-performance relationship. The predictions were tested in publicly listed Australian organizations using archival quantitative data with a longitudinal research design. The results show partial support for the positive linear and inverted U-shaped curvilinear predictions as well as for the proposed moderating effect of industry type. The curvilinear relationship indicates that different proportions of organizational gender diversity have different effects on organizational performance, which may be attributed to different dynamics as suggested by the resource-based view and self-categorization and social identity theories. The results help reconcile the inconsistent findings of past research that focused on the linear gender diversity-performance relationship. The findings also show that industry context can strengthen or weaken the effects of organizational gender diversity on performance.

Do programs to improve business performance in small and medium manufacturing enterprise improve opportunity recognition?

Increasing awareness of the benefits of stimulating entrepreneurial behaviour in small and medium enterprises has fostered strong interest in innovation programs. Recently many western countries have invested in design innovation for better firm performance. This research presents some early findings from a study of companies which participated in an holistic approach to design innovation, where the outcomes include better business performance and better market positioning in global markets. Preliminary findings from in-depth semi-structured interviews indicate the importance of firm openness to new ways of working and developing new processes of strategic entrepreneurship. Implications for theory and practice are discussed.

Design and development of automatic visual inspection system for PCB manufacturing

Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. This paper proposes two inspection modules for an automatic solder joint classification system. The “front-end” inspection system includes illumination normalisation, localisation and segmentation. The “back-end” inspection involves the classification of solder joints using the Log Gabor filter and classifier fusion. Five different levels of solder quality with respect to the amount of solder paste have been defined. The Log Gabor filter has been demonstrated to achieve high recognition rates and is resistant to misalignment. This proposed system does not need any special illumination system, and the images are acquired by an ordinary digital camera. This system could contribute to the development of automated non-contact, non-destructive and low cost solder joint quality inspection systems.

Manufacturing practices and performances: A Malaysian study

The purpose of this study is to identify the most common manufacturing practices adopted by the Malaysian manufacturers, company performance factors and relationship between practices and performances. To fulfil the study objectives, 400 manufacturers were surveyed by a standard 400 questionnaire. Three research methodologies such as descriptive analysis, ANOVA and regression analysis have been employed in this study. The analysis revealed that Malaysian manufacturers focus on optimizing three critical performance factors: product development, less customer return rate and on time delivery (OTD). The most important competitive factor was found to be company reputation and design and manufacturing capacity is the least important factor. The findings also proved that manufacturing practices significantly influence company performances

Manufacturing Yield Improvement by Clustering

Dealing with product yield and quality in manufacturing industries is getting more difficult due to the increasing volume and complexity of data and quicker time to market expectations. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large databases. Growing self-organizing map (GSOM) is established as an efficient unsupervised datamining algorithm. In this study some modifications to the original GSOM are proposed for manufacturing yield improvement by clustering. These modifications include introduction of a clustering quality measure to evaluate the performance of the programme in separating good and faulty products and a filtering index to reduce noise from the dataset. Results show that the proposed method is able to effectively differentiate good and faulty products. It will help engineers construct the knowledge base to predict product quality automatically from collected data and provide insights for yield improvement.

A conceptual model for manufacturing performance improvement

Purpose: Important performance objectives manufacturers sought can be achieved through adopting the appropriate manufacturing practices. This paper presents a conceptual model proposing relationship between advanced quality practices, perceived manufacturing difficulties and manufacturing performances. Design/methodology/approach: A survey-based approach was adopted to test the hypotheses proposed in this study. The selection of research instruments for inclusion in this survey was based on literature review, the pilot case studies and relevant industrial experience of the author. A sample of 1000 manufacturers across Australia was randomly selected. Quality managers were requested to complete the questionnaire, as the task of dealing with the quality and reliability issues is a quality manager’s major responsibility. Findings: Evidence indicates that product quality and reliability is the main competitive factor for manufacturers. Design and manufacturing capability and on time delivery came second. Price is considered as the least important factor for the Australian manufacturers. Results show that collectively the advanced quality practices proposed in this study neutralize the difficulties manufacturers face and contribute to the most performance objectives of the manufacturers. The companies who have put more emphasize on the advanced quality practices have less problem in manufacturing and better performance in most manufacturing performance indices. The results validate the proposed conceptual model and lend credence to hypothesis that proposed relationship between quality practices, manufacturing difficulties and manufacturing performances. Practical implications: The model shown in this paper provides a simple yet highly effective approach to achieving significant improvements in product quality and manufacturing performance. This study introduces a relationship based ‘proactive’ quality management approach and provides great potential for managers and engineers to adopt the model in a wide range of manufacturing organisations. Originality/value: Traditional ways of checking product quality are different types of testing, inspection and screening out bad products after manufacturing them. In today’s manufacturing where product life cycle is very short, it is necessary to focus on not to manufacturing them first rather than screening out the bad ones. This study introduces, for the first time, the idea of relationship based advanced quality practices (AQP) and suggests AQPs will enable manufacturers to develop reliable products and minimize the manufacturing anomalies. This paper explores some of the attributes of AQP capable of reducing manufacturing difficulties and improving manufacturing performances. The proposed conceptual model contributes to the existing knowledge base of quality practices and subsequently provides impetus and guidance towards increasing manufacturing performance.

Design for Manufacturing (DFM) – A case study of repetitive measures

Design for Manufacturing (DFM) is a highly integral methodology in product development, starting from the concept development phase, with the aim of improving manufacturing productivity and maintaining product quality. While Design for Assembly (DFA) is focusing on elimination or combination of parts with other components (Boothroyd, Dewhurst and Knight, 2002), which in most cases relates to performing a function and manufacture operation in a simpler way, DFM is following a more holistic approach. During DFM, the considerable background work required for the conceptual phase is compensated for by a shortening of later development phases. Current DFM projects normally apply an iterative step-by-step approach and eventually transfer to the developer team. Although DFM has been a well established methodology for about 30 years, a Fraunhofer IAO study from 2009 found that DFM was still one of the key challenges of the German Manufacturing Industry. A new, knowledge based approach to DFM, eliminating steps of DFM, was introduced in Paul and Al-Dirini (2009). The concept focuses on a concurrent engineering process between the manufacturing engineering and product development systems, while current product realization cycles depend on a rigorous back-and-forth examine-and-correct approach so as to ensure compatibility of any proposed design to the DFM rules and guidelines adopted by the company. The key to achieving reductions is to incorporate DFM considerations into the early stages of the design process. A case study for DFM application in an automotive powertrain engineering environment is presented. It is argued that a DFM database needs to be interfaced to the CAD/CAM software, which will restrict designers to the DFM criteria. Consequently, a notable reduction of development cycles can be achieved. The case study is following the hypothesis that current DFM methods do not improve product design in a manner claimed by the DFM method. The critical case was to identify DFA/DFM recommendations or program actions with repeated appearance in different sources. Repetitive DFM measures are identified, analyzed and it is shown how a modified DFM process can mitigate a non-fully integrated DFM approach.

Design for manufacturing : a review and case study

Design for Manufacturing (DFM) is a highly integral methodology in product development, starting from the concept development phase, with the aim of improving manufacturing productivity. It is used to reduce manufacturing costs in complex production environments, while maintaining product quality. While Design for Assembly (DFA) is focusing on elimination or combination of parts with other components, which in most cases relates to performing a function and manufacture operation in a simpler way, DFM is following a more holistic approach. Common consideration for DFM are standard components, manufacturing tool inventory and capability, materials compatibility with production process, part handling, logistics, tool wear and process optimization, quality control complexity or Poka-Yoke design. During DFM, the considerable background work required for the conceptual phase is compensated for by a shortening of later development phases. Current DFM projects normally apply an iterative step-by-step approach and eventually transfer to the developer team. The study is introducing a new, knowledge based approach to DFM, eliminating steps of DFM, and showing implications on the work process. Furthermore, a concurrent engineering process via transparent interface between the manufacturing engineering and product development systems is brought forward.

Digital human modelling for vehicle design and manufacturing

Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

Efficiency and productivity of Singapore’s manufacturing sector 2001-2010: An analysis using Simar and Wilson’s (2007) 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 change and Simar and Wilson’s (J Econ, 136:31–64, 2007) bootstrapped truncated regression approach. In the first stage, the nonparametric data envelopment analysis is used to measure technical efficiency. To quantify the economic drivers underlying inefficiencies, the second stage employs a bootstrapped truncated regression whereby bias-corrected efficiency estimates are regressed against explanatory variables. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Most industries were technically inefficient throughout the period except for ‘Pharmaceutical Products’. Sources of efficiency were attributed to quality of worker and flexible work arrangements while incessant use of foreign workers lowered efficiency.