Search results

The purpose of this paper is to propose a new assembly variation analysis model to analyze assembly variation for sheet metal parts. The main focus is to analyze assembly processes based on the method of power balance.

Starting with issues in assembly variation analysis, the review shows the critical aspects of tolerance analysis. The method of influence coefficient (MIC) cannot accurately analyze the relationship between part variations and assembly variations, as the welding point is not a point but a small area. Therefore, new sensitivity matrices are generated based on the method of power balance.

Here two cases illustrate the processes of assembly variation analysis, and the results indicate that new method has higher accuracy than the MIC.

This study is limited to assembly variation analysis for sheet metal parts, which can be used in auto-body and airplane body.

This paper provides a new assembly variation analysis based on the method of power balance.

The purpose of this paper is to focus on optimal sensor placement for the fixture variation diagnosis of compliant sheet metal assembly process. Fixture variations are the main sources for complex automotive body dimensional failures. An effective measurement strategy can help exactly and timely diagnose these fixture variations. Research on sensor placement strategy of compliant sheet metal assembly process is not much stated formerly.

The impact principle of fixture variations is analyzed to set up the relationship between the assembly variation and fixture variations applying the method of influence coefficients and the effective independence (EI) method is used to find the optimal sensor positions based on the impact principle analysis of fixture variations.

The obtained fixture variation sensitivity matrix describes the influence of fixture variations to compliant sheet metal assembly variation and can be used for diagnosing fixture variations. The EI method can effectively solve the optimal sensor positions for compliant sheet metal assembly by a case demonstration.

The proposed method can solve the sensor placement of online assembly station for diagnosing fixture variations. It takes the compliant characteristics of sheet metal parts into account and the sensor information has much greater diagnosability than that from applying other methods.

This paper seeks to present research into the development of a theoretical model for making more informed decisions for the management of variations in building projects. Primarily, the study proposes six principles of effective variation management, which would be helpful for building professionals in assessing and taking proactive measures for reducing the adverse impact of variations.

Based on the principles of effective variation management, a theoretical framework for management of variation orders was developed. The stages presented in the theoretical framework were grouped into three main phases – screening, choice of promising alternatives, and dominance building. Based on the theoretical framework, a model for management of variations was developed.

The theoretical model presents a structured format for management of variation orders. The model will enable the project team to take advantage of beneficial variations when the opportunity arises without an inordinate fear of the negative impacts. By having a systematic way to manage variations, the efficiency of project work and the likelihood of project success should increase.

The study would assist building professionals in developing an effective variation management system. The model emphasized sharing the lessons learned from existing projects with project teams of future projects. The lessons learned should be identified throughout the project life cycle and communicated to current and future project participants. The system would be helpful for them to take proactive measures for reducing variation orders. Hence, the study is valuable for all professionals involved with building projects.

According to the market timing theory, firms try to take advantage of windows of opportunity to raise capital by exploiting temporary cost fluctuations of alternative financing sources. In this context, the main objective of this paper is to examine the influence and persistence of market timing in the financing decisions of Brazilian firms that launched IPOs in the period from 2001 to 2011.

We analyze the influence of past market values on the capital structure of these firms, based on the main models proposed by Baker and Wurgler (2002), adapted to reflect the characteristics of Brazilian firms’ financial statements.

We find evidence of market timing, but this behavior is not sufficiently persistent in the period studied to the point of determining these firms’ capital structure. We believe the fact that Brazilian companies rarely carried out follow-on primary equity issues after floating their capital in the period analyzed, due to the presence of more advantageous financing sources (particularly from the national development bank, BNDES), explains the results. Therefore, Brazilian firms appear to be pay heed to different funding sources, in search of windows of opportunity, to guide their financing decisions and determine their capital structures.

The Brazilian capital market has been developing intensely in recent years, making it increasingly relevant to analyze the financing and investment decisions of the country’s listed companies. The Brazilian literature on capital structure is extensive, but few works have addressed the issue of market timing.

In this paper, we review the literature on pay variation (e.g., pay dispersion, pay compression, pay range) in organizations. Pay variation research has increased markedly in the past two decades and much progress has been made in terms of understanding its consequences for individual, team, and organizational outcomes. Our review of this research exposes several levels-related assumptions that have limited theoretical and empirical progress. We isolate the issues that deserve attention, develop an illustrative multilevel model, and offer a number of testable propositions to guide future research on pay structures.

This study analyzes the rise of genome instability in the life sciences and traces the problematic of instability as it relates to the sociology of health. Genome instability is the study of how genomes change and become variable between generations and within organisms over the life span. Genome instability reflects a significant departure from the Platonic genome imagined during the Human Genome Project. The aim of this chapter is to explain and analyze research on copy number variation and somatic mosaicism to consider the implications of these sciences for sociologists interested in genomics.

This chapter draws on two multi-sited ethnographies of contemporary biomedical science and literature in the sociology of health, science, and biomedicine to document a shift in thinking about the genome from fixed and universal to highly variable and influenced by time and context.

Genomic instability has become a framework for addressing how genomes change and become variable between generations and within organisms over the life span. Instability is a useful framework for analyzing changes in the life sciences in the post-genomic era.

Genome instability requires life scientists to address how differences both within and between individuals articulate with shifting disease categories and classifications. For sociologists, these findings have implications for studies of identity, sociality, and clinical experience.

This is the first sociological analysis of genomic instability. It identifies practical and conceptual implications of genomic instability for life scientists and helps sociologists delineate new approaches to the study of genomics in the post-genomic era.

Variations due to errors and mistakes have caused cost overruns in building projects. Therefore, it is undeniable that the gravity of such variations will be a critical factor in deciding the success of any building project. In addition, the design stage of a building project is considered the most suitable stage to identify and mitigate the causes of potential variations. However, there are no proper mechanisms to minimise the frequency or gravity of variations. Many researchers experienced the promising essence of Poka-Yoke, a mistake-proofing method aimed at increasing efficiency by early detection and eradication of the causes of potential errors. However, less attention has been paid so far to implement Poka-Yoke principles to minimise variations in the building project. Therefore, this study aims to develop a framework to minimise variations in building projects through the integration of the Poka-Yoke principles.

An interpretivism stance is adopted, and a qualitative research approach is used. The data collection technique adopted is semi-structured interviews with ten experts, and the data is analysed using code-based content analysis through NVivo12.

Research findings revealed 23 causes of variations, categorised under client-originated, consultant-originated, contractor-originated and other variations. The identified causes were then mapped with the Poka-Yoke principles to develop the framework. The research findings could prove useful to researchers, academics, government agencies and construction professionals in developing nations that have demographic/cultural and socioeconomic characteristics such as Sri Lanka.

The findings benefitted the Sri Lankan construction sector by minimising the causes of variations. To the best of the authors’ knowledge, this study will be the first of its kind in the Sri Lankan construction industry, leading to a better understanding of the “Poka-Yoke” principle within the building construction context.

A process improvement sampling methodology, known as process variation diagnostic tool (PROVADT), was proposed by Cox et al. (2013). The method was designed to support the objectivity of Six Sigma projects performing the measure-analyse phases of the define-measure-analyse-improve-control cycle. An issue in PROVADT is that it is unable to distinguish between measurement and product variation in the presence of a poor Gage repeatability and reproducibility (R&R) result. The purpose of this paper is to improve and address PROVADT’s sampling structure by enabling a true Gage R&R as part of its design.

This paper derives an enhanced PROVADT method by examining the theoretical sampling constraints required to perform a Gage R&R study. The original PROVADT method is then extended to fulfil these requirements. To test this enhanced approach, it was applied first to a simulated manufacturing process and then in two industry case studies.

The results in this paper demonstrates that enhanced PROVADT was able to achieve a full Gage R&R result. This required 20 additional measurements when compared to the original method, but saved up to ten additional products and 20 additional measurements being taken in future experiments if the original method failed to obtain a valid Gage R&R. These benefits were highlighted in simulation and industry case studies.

The work into the PROVADT method aims to improve the objectivity of early Six Sigma analyses of quality issues, which has documented issues.

This paper develops a new decomposition method of the housing market variations to analyse the housing dynamics of the Australian eight capital cities.

This study reviews the prior research on analysing the housing market variations and classifies the previous methods into four main models. Based on this, the study develops a new decomposition of the variations, which is made up of regional information, home‐market information and time information. The panel data regression method, unit root test and F test are adopted to construct the model and interpret the housing market variations of the Australian capital cities.

This paper suggests that the Australian home‐market information has the same elasticity to the housing market variations across cities and time. In contrast, the elasticities of the regional information are distinguished. However, similarities exit in the west and north of Australia or the south and east of Australia. The time information contributes differently along the observing period, although the similarities are found in certain periods.

This paper introduces the housing market variation decomposition into the research of housing market variations and develops a model based on the new method of the housing market variation decomposition.