Assembly line balancing the comparison of COMSOAL and MSNSH technique in Motorcycle manufacturing company

Today’s highly competitive market influences the manufacturing industry to improve their production systems to become the optimal system in the shortest cycle time as possible. One of most common problems in manufacturing systems is the assembly line balancing problem. The assembly line balancing problem involves task assignments to workstations with optimum line efficiency. The line balancing technique, namely “COMSOAL”, is an abbreviation of “Computer Method for Sequencing Operations for Assembly Lines”. Arcus initially developed the COMSOAL technique in 1966 [1], and it has been mainly applied to solve assembly line balancing problems [6]. The most common purposes of COMSOAL are to minimise idle time, optimise production line efficiency, and minimise the number of workstations. Therefore, this project will implement COMSOAL to balance an assembly line in the motorcycle industry. The new solution by COMSOAL will be used to compare with the previous solution that was developed by Multi‐Started Neighborhood Search Heuristic (MSNSH), which will result in five aspects including cycle time, total idle time, line efficiency, average daily productivity rate, and the workload balance. The journal name “Optimising and simulating the assembly line balancing problem in a motorcycle manufacturing company: a case study” will be used as the case study for this project [5].

Preface to special issue on digital human modelling for vehicle design and manufacturing

The automotive industry has been the focus of digital human modeling (DHM) research and application for many years. In the highly competitive marketplace for personal transportation, the desire to improve the customer’s experience has driven extensive research in both the physical and cognitive interaction between the vehicle and its occupants. Human models provide vehicle designers with tools to view and analyze product interactions before the first prototypes are built, potentially improving the design while reducing cost and development time. The focus of DHM research and applications began with prediction and representation of static postures for purposes of driver workstation layout, including assessments of seat adjustment ranges and exterior vision. Now DHMs are used for seat design and assessment of driver reach and ingress/egress. DHMs and related simulation tools are expanding into the cognitive domain, with computational models of perception and motion, and into the dynamic domain with models of physical responses to ride and vibration. Moreover, DHMs are now widely used to analyze the ergonomics of vehicle assembly tasks. In this case, the analysis aims to determine whether workers can be expected to complete the tasks safely and with good quality. This preface provides a review of the literature to provide context for the nine new papers presented in this special issue.

Towards success in higher education in engineering and technology : a coaching approach to develop holistic graduates

There is a growing gap between engineering practice and engineering education that may be contributing to less engineers practicing in industry. Coaching approach to learning and teaching has been proven to be an effective way to develop people in the workplace. A pilot coaching program is offered to Engineering and Technology students in Queensland University of Technology to enable holistic growth in order to better integrate them to the work force and society at large. The results and findings of this program will be published once the program has been completed

Re-use of domain knowledge to provide confidence for adoption of off-site manufacturing for construction in Australia

Many construction industry decision-makers believe there is a lack of off-site manufacture (OSM) adoption for non-residential construction in Australia. Identification of construction business process was considered imperative in order to assist decision-makers to increase OSM utilisation. The premise that domain knowledge can be re-used to provide an intervention point in the construction process led a team of researchers to construct simple base-line process models for the complete construction process, segmented into six phases. Sixteen domain knowledge industry experts were asked to review the construction phase base-line models to answer the question “Where in the process illustrated by this base-line model phase is an OSM task?”. Through an iterative and generative process a number of off-site manufacture intervention points were identified and integrated into the process models. The re-use of industry expert domain knowledge provided suggestions for new ways to do basic tasks thus facilitating changes to current practice. It is expected that implementation of the new processes will lead to systemic industry change and thus a growth in productivity due to increased adoption of OSM.

The moderating effect of knowledge sharing on the relationship between manufacturing activities and business performance

This paper investigates the critical role of knowledge sharing (KS) in leveraging manufacturing activities, namely integrated supplier management (ISM) and new product development (NPD) to improve business performance (BP) within the context of Taiwanese electronic manufacturing companies. The research adopted a sequential mixed method research design, which provided both quantitative empirical evidence as well as qualitative insights, into the moderating effect of KS on the relationships between these two core manufacturing activities and BP. First, a questionnaire survey was administered, which resulted in a sample of 170 managerial and technical professionals providing their opinions on KS, NPD and ISM activities and the BP level within their respective companies. On the basis of the collected data, factor analysis was used to verify the measurement model, followed by correlation analysis to explore factor interrelationships, and finally moderated regression analyses to extract the moderating effects of KS on the relationships of NPD and ISM with BP. Following the quantitative study, six semi-structured interviews were conducted to provide qualitative in-depth insights into the value added from KS practices to the targeted manufacturing activities and the extent of its leveraging power. Results from quantitative statistical analysis indicated that KS, NPD and ISM all have a significant positive impact on BP. Specifically, IT infrastructure and open communication were identified as the two types of KS practices that could facilitate enriched supplier evaluation and selection, empower active employee involvement in the design process, and provide support for product simplification and the modular design process, thereby improving manufacturing performance and strengthening company competitiveness. The interviews authenticated many of the empirical findings, suggesting that in the contemporary manufacturing context KS has become an integral part of many ISM and NPD activities and when embedded properly can lead to an improvement in BP. The paper also highlights a number of useful implications for manufacturing companies seeking to leverage their BP through innovative and sustained KS practices.

Identifying key enablers to improve business performance in Taiwanese electronic manufacturing companies

Purpose – Integrated supplier management (ISM), new product development (NPD) and knowledge sharing (KS) practices are three primary business activities utilised to enhance manufacturers' business performance (BP). The purpose of this paper is to empirically investigate the relationships between these three business activities (i.e. ISM, NPD, KS) and BP in a Taiwanese electronics manufacturing context. Design/methodology/approach – A questionnaire survey is first administered to a sample of electronic manufacturing companies operating in Taiwan to elicit the opinions of technical and managerial professionals regarding business activities and BP within their companies. A total of 170 respondents from 83 companies respond to the survey. Factor, correlation and path analysis are undertaken on this quantitative data set to derive the key factors which leverage business outcomes in these companies. Following empirical analysis, six semi-structured interviews are undertaken with manufacturing executives to provide qualitative insights into the underlying reasons why certain business activity factors are the strongest predictors of BP. Findings – The investigation shows that the ISM, NPD and KS constructs all play an important role in the success of company operations and creating business outcomes. Specifically, the key factors within these constructs which influenced BP are: supplier evaluation and selection; design simplification and modular design; information technology infrastructure and systems and open communication. Accordingly, sufficient financial and human resources should be allocated to these important activities to derive accelerated rates of improved BP. These findings are supported by the qualitative interviews with manufacturing executives. Originality/value – The paper depicts the pathways to improved manufacturing BP, through targeting efforts into the above-mentioned factors within the ISM, NPD and KS constructs. Based on the empirical path model, and the specific insights derived from the explanatory interviews with manufacturing executives, the paper also provides a number of practical implications for manufacturing companies seeking to enhance their BP through improved operational activities.

Empirical study to identify the key business activities contributing to manufacturing business performance

Purpose: Within the context of high global competitiveness, knowledge management (KM) has proven to be one of the major factors contributing to enhanced business outcomes. Furthermore, knowledge sharing (KS) is one of the most critical of all KM activities. From a manufacturing industry perspective, supply chain management (SCM) and product development process (PDP) activities, require a high proportion of company resources such as budget and manpower. Therefore, manufacturing companies are striving to strengthen SCM, PDP and KS activities in order to accelerate rates of manufacturing process improvement, ultimately resulting in higher levels of business performance (BP). A theoretical framework along with a number of hypotheses are proposed and empirically tested through correlation, factor and path analyses. Design/methodology/approach: A questionnaire survey was administered to a sample of electronic manufacturing companies operating in Taiwan to facilitate testing the proposed relationships. More than 170 respondents from 83 organisations responded to the survey. The study identified top management commitment and employee empowerment, supplier evaluation and selection, and design simplification and modular design as the key business activities that are strongly associated with the business performance. Findings: The empirical study supports that key manufacturing business activities (i.e., SCM, PDP, and KS) are positively associated with BP. The findings also evealed that some specific business activities such as SCMF1,PDPF2, and KSF1 have the strongest influencing power on particular business outcomes (i.e., BPF1 and BPF2) within the context of electronic manufacturing companies operating in Taiwan. Practical implications: The finding regarding the relationship between SCM and BP identified the essential role of supplier evaluation and selection in improving business competitiveness and long term performance. The process of forming knowledge in companies, such as creation, storage/retrieval, and transfer do not necessarily lead to enhanced business performance; only through effectively applying knowledge to the right person at the right time does. Originality/value: Based on this finding it is recommended that companies should involve suppliers in partnerships to continuously improve operations and enhance product design efforts, which would ultimately enhance business performance. Business performance depends more on an employee’s ability to turn knowledge into effective action.

Knowledge sharing for strengthening manufacturing operation and business performance

Manufacturing companies have strived to enhance managerial and technical capabilities to improve business performance. Building these capabilities requires effective share of knowledge - the strategic resource. Specifically, knowledge sharing (KS) between different manufacturing departments can improve manufacturing processes since leveraging organisational knowledge plays an enssential role in achieving competitive advantage. This paper presents an empirical investigation into the impact of KS on the effectiveness of supply chain management (SCM) and the product development process (PDP) in achieving desired business performance (BP). A questionnaire survey was administered from electronic manufacturing companies operating in Taiwan. 168 valid responses were received and used to statistically examine the relationships between the concepts (SCM, PDP, KS, BP). The study findings reveal that within the Taiwanese electronic manufacturing companies KS is an essential enabler for facilitating the effectiveness of SCM and PDP in achieving desired BP.

Improving opportunity recognition and business performance in small and medium manufacturing enterprises through design innovation programs

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 that participated in a 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 to developing new processes of strategic entrepreneurship. Implications for theory and practice are discussed.

Electrospinning and additive manufacturing : converging technologies

A well-engineered scaffold for regenerative medicine, which is suitable to be translated from the bench to the bedside, combines inspired design, technical innovation and precise craftsmanship. Electrospinning and additive manufacturing are separate approaches to manufacturing scaffolds for a variety of tissue engineering applications. A need to accurately control the spatial distribution of pores within scaffolds has recently resulted in combining the two processing methods, to overcome shortfalls in each technology. This review describes where electrospinning and additive manufacturing are used together to generate new porous structures for biological applications.

Leveraging power of learning capability upon manufacturing operations

Learning capability (LC) is a special dynamic capability that a firm purposefully builds to develop a cognitive focus, so as to enable the configuration and improvement of other capabilities (both dynamic and operational) to create and respond to market changes. Empirical evidence regarding the essential role of LC in leveraging operational manufacturing capabilities is, however, limited in the literature. This study takes a routine-based approach to understand capability, and focuses on demonstrating leveraging power of LC upon two essential operational capabilities within the manufacturing context, i.e., operational new product development capability (ONPDC), and operational supplier integration capability (OSIC). A mixed-methods research framework was used, which combines sources of evidence derived from a survey study and a multiple case study. This study identified high-level routines of LC that can be designed and controlled by managers and practitioners, to reconfigure underlying routines of ONPDC and OSIC to achieve superior performance in a turbulent environment. Hence, the study advances the notion of knowledge-based dynamic capabilities, such as LC, as routine bundles. It also provides an impetus for managing manufacturing operations from a capability-based perspective in the fast changing knowledge era.

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.

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.

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.