Improve Process Capability Research Articles

Quality Assurance through Process Improvement - A Concise Review

The past two decades has seen the realization of the manufacturing firms towards quality consciousness. The various firms worldwide employed the statistical tools for minimizing the deviations and subsequently the number of rejects of the manufactured parts. In this process, more prominence is laid on prevention of defects rather than detecting and rejecting the defect in the usual traditional end inspection quality check. This review paper witnesses the procedures involved in the improvement of the manufacturing process capability and focuses on achieving quality assurance through sustained improvement in the manufacturing process. The different methodologies for sustained improvement in manufacturing process across varied industrial sectors, are identified, discussed and presented. The nuances of enhanced product quality levels through process capability improvement work performed in varied areas of industrial manufacturing are also captured.

Improving the Clinical-care Pathway of an Ayurvedic Hospital: A Teaching Case for Developing Process Improvement Capabilities

Business Process Management (BPM) is a topic that has received immense attention in information systems research and practice. While its adoption has been increasing rapidly, many companies struggle to find BPM professionals with the appropriate skills, hence BPM education has been an area of increasing interest as well. One big challenge for BPM education is the lack of teaching resources. Appropriately written BPM teaching cases derived from real-life case scenarios has been recognised as a valuable means to address this gap. Yet, teaching cases that are rich in context dedicated to BPM are still scarce. This teaching case, specifically developed for business process improvement education purposes, is designed as a rich resource to address this gap. Teaching notes with an extensive set of multimedia ancillary material are also available to instructors upon request. This case study is based on a real-life patient-care process of a national Ayurvedic hospital in Sri Lanka. With its position as the leading national institute for Ayurvedic research and teaching, the hospital has the potential to make striding impacts with Ayurvedic innovations both nationally and globally. This narrative describes the current patient-care process in detail, challenging students to analyse the current process and derive justifiable high-impact creative/innovative recommendations that are feasible to the case's context and improve business processes at the hospital.

Determinants of success in Shared Savings Programs: An analysis of ACO and market characteristics

BackgroundMedicare's Accountable Care Organization (ACO) programs introduced shared savings to traditional Medicare, which allow providers who reduce health care costs for their patients to retain a percentage of the savings they generate. ObjectiveTo examine ACO and market factors associated with superior financial performance in Medicare ACO programs. MethodsWe obtained financial performance data from the Centers for Medicare and Medicaid Services (CMS); we derived market-level characteristics from Medicare claims; and we collected ACO characteristics from the National Survey of ACOs for 215 ACOs. We examined the association between ACO financial performance and ACO provider composition, leadership structure, beneficiary characteristics, risk bearing experience, quality and process improvement capabilities, physician performance management, market competition, CMS-assigned financial benchmark, and ACO contract start date. We examined two outcomes from Medicare ACOs’ first performance year: savings per Medicare beneficiary and earning shared savings payments (a dichotomous variable). ResultsWhen modeling the ACO ability to save and earn shared savings payments, we estimated positive regression coefficients for a greater proportion of primary care providers in the ACO, more practicing physicians on the governing board, physician leadership, active engagement in reducing hospital re-admissions, a greater proportion of disabled Medicare beneficiaries assigned to the ACO, financial incentives offered to physicians, a larger financial benchmark, and greater ACO market penetration. No characteristic of organizational structure was significantly associated with both outcomes of savings per beneficiary and likelihood of achieving shared savings. ACO prior experience with risk-bearing contracts was positively correlated with savings and significantly increased the likelihood of receiving shared savings payments. ConclusionsIn the first year, performance is quite heterogeneous, yet organizational structure does not consistently predict performance. Organizations with large financial benchmarks at baseline have greater opportunities to achieve savings. Findings on prior risk bearing suggest that ACOs learn over time under risk-bearing contracts. ImplicationsGiven the lack of predictive power for organizational characteristics, CMS should continue to encourage diversity in organizational structures for ACO participants, and provide alternative funding and risk bearing mechanisms to continue to allow a diverse group of organizations to participate. Level of evidenceIII

A conceptual hybrid framework for industrial process improvement: integrating Taguchi methods, Shainin System and Six Sigma

Design of Experiments (DoE) has evolved as powerful industrial statistics tool for managing and improving processes in diverse industries. The three broad approaches of DoE in practice: classical or traditional methods, Taguchi methods and Shainin System (SS), have their merits and demerits for a extensive industrial experimentation. Nonetheless, the power of these DoE approach is not fully harnessed in established process improvement frameworks in industries. On the other side, Six Sigma DMAIC is a well-accepted methodology for improving process capability through focus on customer’s requirement (CTQ). The use of DoE in traditional DMAIC framework is limited to quantification of influence factors on CTQ. To offer a contribution to this paucity, this paper proposed a conceptual Six Sigma/DOE hybrid framework aiming to integrate SS, Taguchi methods and Six Sigma DMAIC for process improvement in complex industry environment. A case on improving DF generation process in shock absorber assembly was developed to validate the effectiveness of the framework for intricate problem-solving.

MCCB warm adjustment testing concept

This paper presents an experimental investigation in to operating of thermal protection device behavior from an MCCB (Molded Case Circuit Breaker). One of the main functions of the circuit breaker is to assure protection for the circuits where mounted in for possible overloads of the circuit. The tripping mechanism for the overload protection is based on a bimetal movement during a specific time frame. This movement needs to be controlled and as a solution to control this movement we choose the warm adjustment concept. This concept is meant to improve process capability control and final output. The warm adjustment device design will create a unique adjustment of the bimetal position for each individual breaker, determined when the testing current will flow thru a phase which needs to trip in a certain amount of time. This time is predetermined due to scientific calculation for all standard types of amperages and complies with the IEC 60497 standard requirements.

Armentum: a hybrid direct search optimization methodology

Design of experiments (DOE) offers a great deal of benefits to any manufacturing organization, such as characterization of variables and sets the path for the optimization of the levels of these variables (settings) trough the Response surface methodology, leading to process capability improvement, efficiency increase, cost reduction. Unfortunately, the use of these methodologies is very limited due to various situations. Some of these situations involve the investment on production time, materials, personnel, equipment; most of organizations are not willing to invest in these resources or are not capable because of production demands, besides the fact that they will produce non-conformant product (scrap) during the process of experimentation. Other methodologies, in the form of algorithms, may be used to optimize a process. Known as direct search methods, these algorithms search for an optimum on an unknown function, trough the search of the best combination of the levels on the variables considered in the analysis. These methods have a very different application strategy, they search on the best combination of parameters, during the normal production run, calculating the change in the input variables and evaluating the results in small steps until an optimum is reached. These algorithms are very sensible to internal noise (variation of the input variables), among other disadvantages. In this paper it is made a comparison between the classical experimental design and one of these direct search methods, developed by Nelder and Mead (1965), known as the Nelder Mead simplex (NMS), trying to overcome the disadvantages and maximize the advantages of both approaches, trough a proposed combination of the two methodologies.

Aluminium hot extrusion process capability improvement using Six Sigma

Aluminium hot extrusion process capability improvement using Six Sigma

Development of an Innovative Tool Wear Monitoring System for Zero-Defect Manufacturing

High speed machining (HSM) is a technology employed in various industries and is characterised by high flexibility regarding geometrical forms, high productivity as well, as improved workpiece surface quality. In order to exploit the full potential of HSM, the most significant challenges which must be overcome are the frequent process disruptions and the high tool wear rates. This paper outlines a feasibility study of improving the efficiency in the utilisation of HSM by developing an innovative tool wear monitoring system interconnected with an intelligent adaptive control system. The tool wear monitoring system would achieve accuracy and reliability on an unseen level for the on-line quantification of tool wear by integrating indirect measurement methods, sophisticated wear models and intelligent computational methods. The adaptive control system connected with the machine tool will use the tool wear information in order to determine the most appropriate moment for tool change while balancing maximum workpiece quality and maximum tool life. The optimised use of tools will enable stable workpiece quality and significant cost savings. Through the real-time adaptation of cutting parameters, an optimised tool change can be achieved despite varying process parameters. The proposed system will be portable and adaptable to diverse machine tool controls and machine tools, independent of the manufacturer. It will be applicable to various workpiece and tool types, with minimised learning effort required due to the use of intelligent descriptors to describe the wear influencing variables. The system would enable end-users to efficiently use HSM technology. Its benefit in the form of improved process capability and additional cost savings could be quite vital in future projects within the automotive mould and die industries.

Competitive investments in cost reducing process improvement: The role of managerial incentives and spillover learning

We study the rivalry between two firms and consider the effect of spillovers when the firms' operations and technology managers are given bonuses for cost reduction. We model a game in which the firm owners independently offer their manager a bonus to stimulate cost reducing process improvement before the process improvement and production stage, and draw a comparison with the game in which these bonuses are not used. Several outcomes contrast strongly with existing literature. We find that cost reduction bonuses are generally only positive in equilibrium when spillovers are less than 50%. In case spillovers are higher, cost reduction bonuses are only positive when a firm's process improvement capability is relatively high. Also we find that the sensitivity of process improvement levels in the spillover parameter crucially alters when cost reduction bonuses are introduced. Prisoner’s dilemma occurs in case spillovers are less than 50%, or when spillovers are higher and process improvement capability is relatively high.

Risk Assessment of Business Process Re-Engineering Projects

Business Process Re-engineering (BPR) inevitably involves change. However, modern business organizations are extremely complex. Setting improvement targets in BPR too high without considering the company’s capability and its external and internal interactions will have little chance of achieving the set targets, which means project failure. Unfortunately, forecasting of the BPR outcomes is currently a wild guess to management. This paper describes a risk model that estimates a process improvement capability score and integrates with a performance effectiveness function to assess the likelihood of meeting performance gain targets from process improvement projects undertaken by companies. The risk assessment can assist management to set more realistic performance gain targets for process improvement projects with a better chance of success.

Improvement of Paint Thickness in Electro Deposition Painting Process of Truck Manufacturing

The objective of this research is to improve process capability and reduce production cost related to thickness of paint from Electro Deposition Painting (EDP) process. To achieve the objective, Six Sigma method was applied to find out the optimal setting of significant process factors, which are concentration of pigment in EDP paint, dipping time, and dipping voltage. Design of experiment technique with Central Composite Design type helped indicate the optimal setting of the three factors, which yielded the target EDP coating thickness with a minimal production cost. With this optimal setting, the process capability index (Cpk) increased from 0.61 to 1.99, and the production cost is expected to reduce by 1,730,498 THB per year.

Process improvement capability index with cost – A modeling method of mathematical programming

To improve productivity and remain competitive, businesses nowadays introduce the process capability index (Cpm) to evaluate the quality of their products in an effort to improve them and cut down on operation costs. This is because Cpm can clearly reflect process loss and yield percentage (yield%) that it is widely used in the industry. When suppliers’ process capability is found to be limited in terms of Cpm, an improvement in product quality is required and the cost of the improvement varies depending on the source of loss. Though Cpm is a very good index for the evaluation of process capability, it is unable to reflect suppliers’ improvement costs. Thus, this paper takes a reduction in the improvement cost into consideration and proposes the process improvement capability index (CPIM). The mathematical programming model is then used to assess the confidence interval of index CPIM to overcome the problem of complicated estimation of index CPIM. With CPIM, manufacturers are able to evaluate suppliers’ ability in process improvement, particularly when the suppliers’ process capability is found to be limited, to effectively reduce suppliers’ improvement costs, to improve the quality of products, to enhance productivity and finally to achieve the goal of sustainable operations.

The role of TQM in strategic product innovation: an empirical assessment

Purpose– The purpose of this paper is to study the effect of total quality management (TQM) resources on strategic product innovation. It addresses the apparent tension between quality management and innovation management and seeks empirical support for the proposition that quality management resources can be used to support strategic innovation. Based on resource-based view, it defines key resources that firms develop during implementation of TQM systems: TQM culture, product design capability, and process improvement capability – and assesses the role of these resources in the success of product innovation.Design/methodology/approach– A survey of 112 manufacturing firms was conducted and the resulting data were analyzed using partial least squares (PLS) to determine how TQM constructs affect strategic product innovation.Findings– The main finding suggests that only product design capability contributes to strategic product innovation. TQM culture has a direct influence on process improvement and product design capabilities but not on product innovation. The effect of innovation capability and innovation orientation on product innovation was only supported for innovation capability. The effect of innovation orientation is mediated by the development of innovation capability.Research limitations/implications– The paper focusses on the level of maturity of capability development without taking into consideration the time since adoption. Also, the measure of product innovation is based on the degree of product newness but does not dichotomize in terms of radical vs incremental. Several arguments supporting a negative relationship between TQM and innovation often refer to radical or breakthrough innovation. It would be interesting to test the model while distinguishing between radical and incremental innovation. The use of cross-sectional data is a methodological limitation.Practical implications– The results suggest that managers can leverage their quality management systems to support product innovation. In particular, the ability to design quality into products leads to higher levels of strategic production innovation. The successful deployment of TQM capabilities requires an integrative and well-structured approach, involving top leadership engagement of employees and customer orientation. While TQM culture is critical to the development of quality management capabilities, it does not directly affect the innovativeness of a firm.Originality/value– The paper explores the relationship between quality management systems and strategic product innovation. Further work is needed to test whether TQM effect on strategic innovation is different for radical and incremental products, and for other innovation outcomes such as process and service innovation.

A Comparison Study of Single‐Scale and Multiscale Approaches for Data‐Driven and Model‐Based Online Denoising

Signal denoising is a pervasive operation in most online applications, such as engineering process control and online optimization, strongly affecting the outcome of these higher‐level tasks and impacting the overall variability exhibited by processes and products. Therefore, it plays a fundamental role in improving process capability, which is, however, often overlooked. In this work, we compare the performance of different types of currently available online denoising filters using a variety of test signals that represent the diversity of situations likely to be found in practice, properly corrupted with additive noise of varying magnitudes. Both single‐scale/multiscale, data‐driven/model‐based and time domain/frequency domain, online filtering approaches were contemplated, in what is, to the best of the authors knowledge, the more extensive comparison study conducted on online denoising (or filtering) methodologies. A new class of multiscale denoising algorithms is also considered in this study, based on the online wavelet multiresolution decomposition. In this context, we propose and test a new formulation, called the online multiscale hybrid Kalman filter. After proper tuning, the methods are tested and their performances compared. As a result of the comparison study, clear guidelines are provided for practitioners on the use of online denoising methodologies, which allow for a better management of the impact of the propagation of unstructured components of variability in the final outcome of the processes. Copyright © 2014 John Wiley & Sons, Ltd.

Using Visual Data Mining to Enhance the Simple Tools in Statistical Process Control: A Case Study

Statistical process control (SPC) is a collection of problem‐solving tools used to achieve process stability and improve process capability through variation reduction. Because of its sound statistical basis and intuitive use of visual displays, SPC has been extensively used in manufacturing and health care and service industries. Deploying SPC involves both a technical aspect and a proper environment for continuous improvement activities based on management support and worker empowerment. Many of the commonly used SPC tools, including histograms, fishbone diagrams, scatter plots, and defect concentration diagrams, were proposed prior to the advent of microcomputers as efficient methods to record and visualize data for single (or few) variable(s) processes. As the volume, variety, and velocity of data continues to evolve, there are opportunities to supplement and improve these methods for understanding and visualizing process variation. In this paper, we propose enhancements to some of the basic quality tools that can be easily applied with a desktop computer. We demonstrate how these updated tools can be used to better characterize, understand, and/or diagnose variation in a case study involving a US manufacturer of structural tubular metal products. Finally, we create the quality visualization toolkit to allow practitioners to implement some of these visualization tools without the need for training, extensive statistical background, and/or specialized statistical software. Copyright © 2014 John Wiley & Sons, Ltd.

A DMAIC approach for process capability improvement an engine crankshaft manufacturing process

The define–measure–analyze–improve–control (DMAIC) approach is a five-strata approach, namely DMAIC. This approach is the scientific approach for reducing the deviations and improving the capability levels of the manufacturing processes. The present work elaborates on DMAIC approach applied in reducing the process variations of the stub-end-hole boring operation of the manufacture of crankshaft. This statistical process control study starts with selection of the critical-to-quality (CTQ) characteristic in the define stratum. The next stratum constitutes the collection of dimensional measurement data of the CTQ characteristic identified. This is followed by the analysis and improvement strata where the various quality control tools like Ishikawa diagram, physical mechanism analysis, failure modes effects analysis and analysis of variance are applied. Finally, the process monitoring charts are deployed at the workplace for regular monitoring and control of the concerned CTQ characteristic. By adopting DMAIC approach, standard deviation is reduced from 0.003 to 0.002. The process potential capability index (CP) values improved from 1.29 to 2.02 and the process performance capability index (CPK) values improved from 0.32 to 1.45, respectively.

Understanding pharmaceutical quality by design.

This review further clarifies the concept of pharmaceutical quality by design (QbD) and describes its objectives. QbD elements include the following: (1) a quality target product profile (QTPP) that identifies the critical quality attributes (CQAs) of the drug product; (2) product design and understanding including identification of critical material attributes (CMAs); (3) process design and understanding including identification of critical process parameters (CPPs), linking CMAs and CPPs to CQAs; (4) a control strategy that includes specifications for the drug substance(s), excipient(s), and drug product as well as controls for each step of the manufacturing process; and (5) process capability and continual improvement. QbD tools and studies include prior knowledge, risk assessment, mechanistic models, design of experiments (DoE) and data analysis, and process analytical technology (PAT). As the pharmaceutical industry moves toward the implementation of pharmaceutical QbD, a common terminology, understanding of concepts and expectations are necessary. This understanding will facilitate better communication between those involved in risk-based drug development and drug application review.

Improvement of Process Capability in a Multistep Machining Process

The work in this paper will present a developed methodology for process capability evaluation and improvement in a multistep machining process. In this methodology, a physical model is developed to describe the complex variation propagation process throughout all steps in a multistep machining process. Then building on this physical model, a process capability index evaluation method is derived. A capability improvement procedure is developed to prioritize process improvement efforts based on the sensitivity analysis of process parameters. Finally, the effectiveness of the proposed methodology is demonstrated in a case study.

Improvement of a Riveting Process Capability with Application of Tools and Methods of the Quality Management

Assessment of a process capability is an important area of the quality management. Quality of produced outputs depends on the quality of the process, in which product characteristics are formed. In considering the capability of the process, the ability of the process should be determined to provide the required quality of products. The required product quality has to meet customer requirements and expectations. For determination of process capability are used methods, which are based on comparing variability of selected product quality characteristics. The smaller the variability of the input factor is, the better is the process capability and therefore a better quality of product is produced. Improvement of process capability and reducing the variability of the product quality characteristics can be achieved by means of applying of statistical methods. Standards for the quality management system require the need of statistical methods application as well as other tools and techniques for improvement in business practice. It is necessary to use statistical methods in measuring, monitoring and process improvement. So can be determined the process variability, identified common and special causes of variability and in consequence to propose corrective actions. The paper describes first theoretical characteristics of capability assessment methods and tools in continuous improvement in industry praxis. With application of chosen statistical methods has been improved capability of the riveting process of clutch disk.

Construction of Cutting Tool Life-cycle Information Management Platform

To improve process capability in manufacture industry, the information of cutting tool life-cycle is vital. The cutting tool life-cycle management was presented. Some key technologies were investigated, including cutting tool resource classification and code technology, etc.. Further more, the cutting tools life-cycle management system was analyzed and designed through IDEF (Integrated computer aided manufacturing definition method ) methodology, and then the key page of TLMS (tool life-cycle management system) was employed according to J2EE (java 2 platformenterprise edition (j2ee)) mode. The information management platform of the cutting tool life-cycle is an effective way to solve its shortage of resources during manufacture.