Continuous Product Improvement Research Articles

Reverse engineering in finite element analysis of the behaviour of lignocellulosic materials subjected to cyclic stresses

In all engineering fields, continuous improvement of products and processes is being pursued. Reverse engineering is a fast and innovative method of converting a physical model into a virtual one based on its physical and mechanical characteristics. The paper aims to develop the geometric and numerical virtual model of the behavior of a lignocellulosic material subjected to cyclical stresses (tensile-compression) based on mechanical characteristics determined through experimental tests. The importance of this study consists of identifying the simulation method by comparing the experimental results with the numerical results (engineering objective) and developing the working methodology with effect in the education for sustainable development. Modeling with the finite element method (FEM) based on the physical model aimed to determine the results spectrum which are interpolating with the experimentally ones. Thus, the CAD model of the real sample was made by attributing its physical and elastic characteristics using the HyperMesh (preprocessing) and HyperWorks software (post-processing). The model was meshed into QUAD4 elements, after which it were simulated the cyclical stresses on tensile-compression in successive stages, keeping in memory of each stage the changes made at the structural level in the previous stage. Finally, the theoretical results were compared with the experimental ones. The obtained results provide information about distribution of stresses and strains on each layer of material according to the type of stress, traction or compression, for each loading cycle. The values obtained with FEA are close to the experimental ones. The minor differences are due to using an approximate decrease of the modulus of elasticity after each stress cycle. To obtained the real values of Young’s Modulus after each cycle would have been necessary a big consumption of samples. The reverse engineering method has the advantage of material economy and the ability to carry out a large number of numerical models to replicate the material’s behavior more accurately to cyclical loading and even improve its properties by designing a new material.

Introduction

Introduction

Prediction of Indoor Temperature and Relative Humidity Based on Cloud Database by Using an Improved BP Neural Network in Chongqing

For continuous improvement of productivity, accurate, stable, and reliable control of temperature and humidity is important in industrial production. Accurate prediction of air temperature and humidity can improve the predictability and stability of air conditioning control systems. In this paper, based on the cloud database of industry settings, an improved prediction model based on backpropagation (BP) neural networks was established to forecast indoor air temperature (IT) and relative humidity (IH) every 10 min and 6–72 h in advance. The experimental building was in Chongqing, a typical humid, hot-summer, and cold-winter area in China. The test data were used to determine the optimal parameters of the neural network model. The experimental results showed that the IT and IH predictions by our model have strong correlations with the actual data, with the coefficients of determination being 0.9897 and 0.9778, respectively. Compared with other literature, our model was more effective in temperature prediction. The presented method can be used for the prediction and control of the indoor temperature and relative humidity in industrial production.

Improvement of the customer satisfaction through Quality Assurance Matrix and QC-Story methods: A case study from automotive industry

Presently, in the automotive industry, the tendency is to adapt permanently to the changes and introduce the market tendency in the new products that leads of the customer satisfaction. Many quality techniques were adopted in this field to continuous improvement of product and process quality and advantages were also gained. The present paper has focused on possibilities that offers the use of Quality Assurance Matrix (QAM) and Quality Control Story (QC Story) to provide largest protection against nonconformities in the production process, throughout a case study in the automotive industry. There is a direct relationship from the QAM to a QC Story analysis. The failures identified using QAM are treated with QC Story methodology. Using this methods, will help to decrease the PPM values and will increase the quality performance and the customer satisfaction.

Comparative Analysis of Construction Process at Building Sites

The accurate measurement of labor productivity data can mean the difference between the success and failure of a building construction project. Due to the sheer diversity and complexity of international building construction practices, minimal research has been performed on comparative labor productivity between countries. In this paper, the authors present a research project that was conducted by comparing the Chinese labor productivity with the U.S. labor productivity in building construction projects. The labor productivity data were collected from different jobsites in the U.S. and China by using a time-study method with established data collection procedures. Furthermore, work sampling in the HVAC system work category was used as a method to gather information about the amount of labor productive and nonproductive work hours spent on construction activities. It is certain that there are many factors affecting productivity in the building construction process. With the lack of timely and effective project quality supervision, construction quality cannot be guaranteed. For this reason, various statistical analysis methods were applied to analyze and compare the collected productivity data from both countries. Findings of this productivity comparison can provide industry practitioners the advancement of knowledge in the Chinese building construction industry and it can support benchmarking and continuous improvement of productivity with a greater efficiency in both the US and Chinese building construction markets.

Computational testing algorithmic procedure of assessment for lifetime performance index of Pareto products under progressive type I interval censoring

Process capability indices had been widely used to evaluate the process performance to the continuous improvement of quality and productivity. When the lifetime of products possesses a one-parameter Pareto distribution, the larger-the-better lifetime performance index is considered. The maximum likelihood estimator is used to estimate the lifetime performance index based on the progressive type I interval censored sample. The asymptotic distribution of this estimator is also investigated. We use this estimator to develop the new hypothesis testing algorithmic procedure in the condition of known lower specification limit. Finally, two practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.

A comprehensive computational multidisciplinary design optimization approach for a tidal power plant turbine

Multidisciplinary design optimization has become a powerful technique to facilitate continuous improvement of complex and multidisciplinary products. Parametric modeling is an essential part with tremendous impact on the flexibility and robustness of multidisciplinary design optimization. This article investigates the effect of relational and non-relational parameterization techniques on the robustness and flexibility of the conceptual design of a multidisciplinary product. Bench marking between relational and non-relational parameterization and their effect on flexibility and robustness indicate that the relational parameterization is an efficient method in the multidisciplinary design optimization process. The inherent properties of the method contribute to an efficient parametric modeling with improved communication between different disciplines. This enhances the performance of the multidisciplinary design optimization process and allows a more flexible and robust design. The considered disciplines are computer-aided design, computational fluid dynamics, finite element analysis, and dynamic simulation. A high-fidelity geometry created in a computer-aided design environment is computer-aided design centric approach and later used in computational fluid dynamics, finite element analysis for a better understanding of the product as it leads to precise outcomes. The proposed approach is implemented for the conceptual design of a novel product, a tidal power plant developed by Minesto AB using a multidisciplinary design optimization process.

A bibliometric analysis of 50 years of worldwide research on statistical process control

Abstract An increasing number of papers on statistical process control (SPC) has emerged in the last fifty years, especially in the last fifteen years. This may be attributed to the increased global competitiveness generated by innovation and the continuous improvement of products and processes. In this sense, SPC has a fundamentally important role in quality and production systems. The research in this paper considers the context of technological improvement and innovation of products and processes to increase corporate competitiveness. There are several other statistical technics and tools for assisting continuous improvement and innovation of products and processes but, despite the limitations in their use in the improvement projects, there is growing concern about the use of SPC. A gap between the SPC technics taught in engineering courses and their practical applications to industrial problems is observed in empirical research; thus, it is important to understand what has been done and identify the trends in SPC research. The bibliometric study in this paper is proposed in this direction and uses the Web of Science (WoS) database. Data analysis indicates that there was a growth rate of more than 90% in the number of publications on SPC after 1990. Our results reveal the countries where these publications have come from, the authors with the highest number of papers and their networks. Main sources of publications are also identified; it is observed that the publications of SPC papers are concentrated in some of the international research journals, not necessarily those with the major high-impact factors. Furthermore, the papers are focused on industrial engineering, operations research and management science fields. The most common term found in the papers was cumulative sum control charts, but new topics have emerged and have been researched in the past ten years, such as multivariate methods for process monitoring and nonparametric methods.

Computational testing algorithmic procedure of assessment for lifetime performance index of products with Weibull distribution under progressive type I interval censoring

The assessing of the lifetime performance is a very important topic in manufacturing or service industries. Process capability indices had been widely used to evaluate the process performance to the continuous improvement of quality and productivity. The lifetimes of products are assumed to have Weibull distribution with a known shape parameter and the larger-the-better lifetime performance index is considered. The maximum likelihood estimator is used to estimate the lifetime performance index based on the progressive type I interval censored sample. The asymptotic distribution of this estimator is also investigated. We use this estimator to develop the new hypothesis testing algorithmic procedure with respect to a lower specification limit. Finally, two practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.

Sensitivity analysis–based dynamic process capability evaluation for small batch production runs

Quantifying the current and expected future performance of a machining process no doubt is essential for continuous improvement of product quality and productivity. However, process capability evaluation for small batch production runs is a challenging work, because the assumptions required by traditional evaluation approaches based on statistical process control techniques are commonly not satisfied in real world. In this article, a sensitivity analysis–based process capability evaluation method for small batch production runs is proposed, and a new capability index is also presented correspondingly. In this method, an error propagation model between machining errors and input errors is first established using weighted least squares support vector machine. Then, the sensitivity distribution of machining errors versus input errors is characterized by a set of eigenvalues and eigenvectors in the variation space of input errors. Third, the safe variation space of input errors is solved according to the specification limits of quality characteristics. Finally, the process capability is evaluated by comparing the fitness between the safe variation space and the tolerance space of input errors. A practical case is addressed to validate the feasibility and effectiveness of the proposed method, and the results demonstrate that the method can measure a real small batch machining process effectively and get rid of the common assumption of independent and identical distribution, which is needed by traditional methods.

Overview of Automotive Core Tools: Applications and Benefits

Continuous improvement of product and process quality is always challenging and creative task in today’s era of globalization. Various quality tools are available and used for the same. Some of them are successful and few of them are not. Considering the complexity in the continuous quality improvement (CQI) process various new techniques are being introduced by the industries, as well as proposed by researchers and academia. Lean Manufacturing, Six Sigma, Lean Six Sigma is some of the techniques. In recent years, there are new tools being opted by the industry, especially automotive, called as Automotive Core Tools (ACT). The intention of this paper is to review the applications and benefits along with existing research on Automotive Core Tools with special emphasis on continuous quality improvement. The methodology uses an extensive review of literature through reputed publications—journals, conference proceedings, research thesis, etc. This paper provides an overview of ACT, its enablers, and exertions, how it evolved into sophisticated methodologies and benefits used in organisations. It should be of value to practitioners of Automotive Core Tools and to academics who are interested in how CQI can be achieved using ACT. It needs to be stressed here that this paper is not intended to scorn Automotive Core Tools, rather, its purpose is limited only to provide a balance on the prevailing positive views toward ACT.

Utilização do AHP para priorização das práticas de TQM na indústria farmacêutica

A Gestão pela Qualidade Total ou Total Quality Management (TQM) consiste em uma estratégia de gestão, que requer o envolvimento e comprometimento de toda organização, na melhoria contínua de produtos e processos, tendo como foco a satisfação do cliente. Este artigo destacou a importância de priorizar algumas práticas da Gestão da Qualidade Total na indústria farmacêutica, auxiliando na sua implantação. Foi utilizado o método de decisão multicriterial AHP (Analytic Hierarchy Process), o qual tem como função estruturar as práticas de TQM de forma hierarquizada. Assim foram avaliadas 17 práticas do TQM, divididas em três categorias (estratégicos, táticos e operacionais). Os resultados sugerem que a Gestão Estratégica foi o fator de maior importância, seguido pelos fatores táticos e operacionais. O presente trabalho atingiu seu objetivo de ajudar gestores do setor farmacêutico a se orientarem de forma eficaz para obter melhor desempenho das práticas do TQM e alcançar os objetivos desejados.

Critical Success Factors In the Implementation of Strategy by the Multinational Corporations in the Pharmaceutical Industry: An Empirical Investigation

Strategy implementation is the key that opens doors to creatively align organizational strategy with its internal support systems that transforms analyzed and formulated strategies into action. An organization in the pharmaceutical business, which is a business that competes in the knowledge economy for discovering and commercializing therapeutic agents, must endeavour to continually develop strategies to protect its intellectual capital and improve performance. Despite this realisation the importance of strategy implementation, is still greatly overshadowed by a focus on the strategy formulation process. Literature available on strategy implementation is very scarce and especially in the pharmaceutical industry. This study, therefore, is poised to explore and determine the critical success factors for strategy implementation among Multinational corporations in the Kenyan pharmaceutical industry. The study was conducted in Kenya in 2014 as a census survey of twelve Multinational pharmaceutical corporations. Data for this survey was collected through the use of structured questionnaires, which were distributed to 36 respondents of which 32 responded an 89% respondent rate. This study was hinged on the dynamics capabilities theory, resource based view theory and the concept of competitive advantage. Data analysis was done using descriptive statistics and factor analysis to a large extent. Results indicate that critical success factors for strategy implementation include; Infrastructure factors; Clear and concise communication of the strategy to the staff, with a variance loading of(0.942)Resource set aside for new strategy,(0.871,variance loading),Planning, co-ordinating, monitoring and delegation of responsibilities for implementation of strategy,(0.970), Organisational structure that is supportive(0.889).Time frame; Specified time frame allocated for strategy implementation(0.971), allocation for obstacles surfaced during implementation that were not envisioned beforehand, environmental factors also emerged as key to this process. For competitive advantage. People-product mix; Possession of detailed knowledge on customers' needs, tastes and preferences by employees, hiring and retraining top talent within the organization, continuous product improvement and innovations, Production of unique products for a specific target market, partnering with customers to produce highly customized products and strategic alliances with key stakeholders in the industry. These factors had implication on theory and practice since they were found to be universal.

Application of the Taguchi method to improve a medical device cutting process

Companies currently are immersed in a highly competitive world; therefore, they must adopt continuous process and product improvement techniques to remain in business and retain loyal customers. This paper presents the analysis of a medical device manufacturing company to determine what factors influence the length variation of plastic tubes in a cutting process. These tubes are part of intensive care sets; therefore, their length and diameter are critical features. Recently, products were rejected for not meeting the tube length specification, causing customer complaints regarding product quality. The Taguchi method was applied to find significant factors that determine the best configuration in the cutting process to approximate this quality characteristic to its desired target value. Important factors and their corresponding best levels were identified. After the proposed process adjustment was implemented, the process capability index (Cpk) increased from 0.90 to 1.58, which indicated a considerable reduction in customer complaints and corresponding costs.

Human, technology, organization and environment – a human factors perspective on performance in forest harvesting

ABSTRACTIn recent years, concern has been raised that the trend of continuous productivity improvements of forest harvesting has stagnated and even declined in the Nordics. This selective literature review therefore examines human factors research with regard to the performance of the harvesting system, and outlines how human factors research can stimulate continued performance improvements. The focus is on implications for mechanized cut-to-length (CTL) operations and, especially, research of importance to the operation of the single grip harvester and the harvester-forwarder system. Most literature for this review was found in the Web of Knowledge and Google Scholar databases or as a consequence of the snowballing approach also applied. A conceptual framework was used to facilitate the analysis of the interrelated elements – Human, Technology, Organization and Environment (HTO-E). The right abilities, skills, techniques and training alone are not sufficient for ensuring high performance of the logging system. To address this discrepancy, education, training, (semi-) automation, shift scheduling, harvester-forwarder cooperation, inter- and intra- organizational knowledge exchange were all recognized as important areas for improvement and development. Great difficulties exist in predicting outcomes when introducing change, for example automation, into a system. However, the consequences of not trying may be detrimental to productivity as well as safety in mechanized forestry. Thus, it is important to research into methods, interfaces, forms of interaction, risk analyses and automation technology. HTO-E and a systems perspective provide a good basis for understanding the work today and making educated predictions for the future.

Partial Substitution of Inorganic with Organic Fertilizer for Enhancement Fresh Fruit Bunch (FFB) Productivity in Oil Palm Plantations

Partial Substitution of Inorganic with Organic Fertilizer for Enhancement Fresh Fruit Bunch (FFB) Productivity in Oil Palm Plantations This paper describes the alternative fertilizer application in oil palm plantations of Riau Province, Indonesia. Expensive Inorganic fertilizer is needed in a considerable amount that farmers seek for alternatives. One of the solutions is by using organic palm residue fertilizer, as it is cheap, much available, and rich in nutrition. Fertilizer application is differentiated based on the four age category: young (3-8 years), juvenile (9-13 years), mature (14-20 years), and old (21-25 years). Three types of fertilizer, which is Inorganic fertilizer, organic fertilizer, and Inorganic fertilizer with partial substitution, was applied to each category. For a one year, several data such as type of fertilizer, fertilizer dose, fertilizing rotation and FFB productivity was observed monthly. The result shows that partial substitution of Inorganic fertilizer with organic fertilizer significantly raise FFB productivity, especially for young (Yplus) and old (Oplus) age category. It yields continuous improvement of FFB productivity, beginning from age young until old. Thus, the productive period of oil palm can last more than 25 years. Besides, better FFB productivity is achieved in young age category compared to usual production.

Beyond Target Costing: Manufacturing Cost Policy Deployment for New Products

The purpose of this paper is to present a method to quantify the costs of potential losses from production processes for new products to prioritize improvement projects based on the target cost and provide data and information for feasibility studies of continuous improvement projects. The specificity of the manufacturing cost policy deployment for new products is to identify the percentage of cost of future production phases which does not add value from a customer perspective, dynamically throughout the product life cycle. The percentage of non-value added cost is based on loss of each manufacturing process and is determined scientifically based on data and facts. Using the proposed method helps manufacturing companies in the acceptance of certain orders which at first glance are unprofitable. Moreover, the proposed method will help develop scenarios for continuous cost reduction after starting production through continuous improvement of productivity and quality required. The empirical results are based on the study during a year and a half in the automotive company, using action research methodology.

A Cloud-Based Framework for Lean Maintenance, Repair, and Overhaul of Complex Equipment

Large, complex, expensive, and long-lived equipment often operate in harsh environments, which leads to the requirements of lifecycle maintenance, repair, and overhaul (MRO). To support the continuous improvement of productivity and to reduce the cost of MRO, this paper developed a cloud-based framework for lean MRO of the equipment with the aforementioned characteristics. A concept and a model of lean MRO are proposed. Taking advantage of cloud-based design and manufacturing (CBDM) into account, an architectural framework of cloud-based MRO is proposed. A case of a lean MRO for continuous casting equipment demonstrates that the proposed cloud-based framework can achieve the goal of lean MRO of complex equipment.

Computational testing algorithmic procedure of assessment for lifetime performance index of products with one-parameter exponential distribution under progressive type I interval censoring

Process capability indices had been widely used to evaluate the process performance to the continuous improvement of quality and productivity. When the lifetime of products possesses a one-parameter exponential distribution, the larger-the-better lifetime performance index is considered. The maximum likelihood estimator is used to estimate the lifetime performance index based on the progressive type I interval censored sample. The asymptotic distribution of this estimator is also investigated. We use this estimator to develop the new hypothesis testing algorithmic procedure in the condition of known lower specification limit. Finally, two practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.

Implementation of ISBT quality indicators in the quality management and haemovigilance systems

Quality indicators are an indispensable tool in quality measurement. Monitoring and analysis of quality indicators, along with implementation of appropriate corrective measures, enable continuous product and service quality improvement. Quality indicators have been used for years in health‐care institutions, while in transfusion medicine, they have only recently received due attention. Since 2010, an array of activities in the field of education on quality indicators, their selection and implementation have been launched under the umbrella of the International Society of Blood Transfusion Working Party on Quality Management. Besides historical review of these activities, the place and role of quality indicators in the quality management and haemovigilance systems, methods of their selection, defining quality objectives and action limits, statistical monitoring and reporting are discussed.