Continuous Improvement Project Research Articles

Toward the successful adoption of Lean Six Sigma in manufacturing organizations: proposing a causal model

PurposeThis paper aims to provide new and valuable insights for organizations that have decided to implement Lean Six Sigma (LSS) as a strategy for continuous improvement in search of business excellence. This objective is achieved through statistically modeling the causal relationships between the critical success factors (CSFs) of LSS for a successful deployment of this strategy.Design/methodology/approachA statistically validated questionnaire was used to collect information from LSS practitioners in manufacturing industries located on Mexico’s northern border. Some hypotheses for relationships between LSS CSFs are developed theoretically first and empirically tested later using the structural equation modeling technique.FindingsProposed relationships between LSS CSFs have been demonstrated to be statistically significant, making clear that this implementation should always begin with a strong and decided participation and commitment of top management. Later, other CSFs must be activated and put into operation in a specified order to increase the probability of a successful implementation reflected in well-executed continuous improvement projects and achieving the expected benefits.Originality/valueThis paper proposes a structural model which has been statistically validated with information directly collected from skilled practitioners who have developed continuous improvement projects using the LSS methodology. Further, some relationships between LSS CSFs that, to the best of the author’s knowledge, had not been demonstrated empirically are now explored and verified in our work.

Reduction of Setup Times in a Metal Fabrication Company Using a Lean-Sigma Approach

Manufacturing companies face demand fluctuations and must deliver the required quantity of parts to their customers within the required time; however, companies face different challenges in fulfilling them. One is technological advances, which make it impossible for them to compete with other countries, such as China, due to financial issues. Therefore, manufacturing companies use continuous improvement methodologies to achieve better performance in their processes. Six Sigma and Lean Manufacturing are some of the best-known approaches. This article briefly presents the application of a lean sigma approach oriented to solving problems. This research proposes a methodology based on Lean Sigma that contrasts what different authors currently do: continuous improvement projects that take up to 12 months to produce results and do not solve a problem. This implementation is conducted in a process that manufactures metal parts and fails to deliver them on time to its customers. Using tools such as the Single Minute Exchange of Die (SMED) in a production line, on-time deliveries were increased from 89 % to 96 %; at the same time, the model change times were reduced by approximately 60 %, which is required for the implementation of this methodology for only four weeks, unlike the traditional six-sigma approach that can take up to 12 months to improve the process.

Using Appreciative Inquiry to Understand Workload Reasonability

This article describes an organizational continuous process improvement project using Appreciative Inquiry to evaluate staff members’ perception of their unreasonable workload, as indicated in the Federal Employee Viewpoint Survey. The goal for approaching the management-directed study was to use AI to frame the conversation around the lifegiving forces aspects AI brings to the organization rather than a traditional continuous process improvement approach in which we would investigate a problem, identify issues, and propose solutions to correct it.

Factors That Impact the Dynamics and Effectiveness of Work Teams during the Implementation of Continuous Improvement Tools in the Manufacturing Industry: A Systematic Literature Review

Currently, because of global competition, companies within the manufacturing industry must implement new organizational and production techniques to compete and stay active. The use of continuous improvement tools has become an opportunity and an effective strategy to achieve this. However, there is evidence that many continuous improvement programs are not successfully implemented due to a lack of information related to human management during the implementation of these projects in the manufacturing industry. In this context, the objective of this research is to identify factors influencing the dynamics and effectiveness of work teams for the implementation and development of continuous improvement tools in the manufacturing industry. A literature review was conducted using the PRISMA method, considering scientific articles related to the main factors that affect the dynamics and effectiveness of work teams in relation to the implementation of continuous improvement tools. From the review and evaluation of the studies, 60 factors were identified that affect the effectiveness of work teams in relation to continuous improvement within the manufacturing industry. Subsequently, a Pareto analysis was conducted on the critical success factors based on the number of occurrences in the analyzed literature, identifying 32 critical success factors considered vital for the implementation of continuous improvement projects. It is concluded that the factors arise from two common elements, the involvement of senior management and the company’s own culture. Therefore, to ensure the effectiveness of work teams and their continuous improvement projects, management must focus attention on this cultural change mainly by providing the necessary resources for the development of the project, establishing an adequate and effective reward system, and, most importantly, directing efforts towards staff empowerment.

Lean monitoring: action research in manufacturing

PurposeThis study aims to study the implementation of lean thinking at the strategic level of an Italian manufacturing company. Companies implementing continuous improvement (CI) projects in their production processes often take the monitoring phase for granted. This research deploys an A3 lean thinking project in the monitoring phase of strategic KPIs upon completion of several ongoing improvement projects.Design/methodology/approachThe research methodology is action research aiming at disseminating the problems that the company is facing. The study relies on the lean action plan developed by Womack and Jones (2003): Planning for lean and Lean action. Lean planning consists of the following steps: find a change agent; get the knowledge; find a lever. Lean action uses the A3 lean approach.FindingsThe company reached high-performance improvements due to the proposed lean action plan.Research limitations/implicationsThis study contributes by presenting a lean action plan in the monitoring phase, highlighting the importance of the lean thinking-monitoring continuum in reducing time waste for faster diagnosis and using action research to analyze and instill reflective learning.Originality/valueThe research relies on the A3 methodology to showcase the benefits that a mature paradigm, often coined to production, still has unexplored potentials.

Six-Sigma Reference Model for Industry 4.0 Implementations in Textile SMEs

The textile and apparel industry is a major contributor to Latin American economies. However, in these economies the industry is characterized by limited technological infrastructure, which has led to inefficient performance and the significant generation of water, material, and product waste through its supply chain (SC). Currently, Industry 4.0 has led to important benefits in manufacturing industries, but its application in the textile field has been limited to few case studies. The present work expands on this aspect with a critical review of Industry 4.0 concepts and principles, and our main contribution consists of an implementation guideline model. The model was based on Six Sigma and the Rothwell and Zegveld model for continuous improvement and innovation projects in manufacturing and business enterprises. In each step, key aspects such as the specific skills of the interdisciplinary team, assessment tools, and implementation/prototyping tools are highlighted. A discussion of a case study is presented to support the applicability of the model for Industry 4.0 pilot projects.

Driving Continuous Improvement in Engineering Projects with AI-Enhanced Agile Testing and Machine Learning

Continuous improvement projects follow unique selection, deployment, and tracking processes. In today’s fast-paced engineering projects, it has become crucial to drive actionable change for continuous improvement to support the delivery of success. Software development has been a major adopter of agile approaches because of the iterative nature of the process and how well it fits the ever-changing goals of engineering projects. This article delves into the topic of how software development and engineering project management may be improved by using AI and ML in Agile testing procedures. With the help of AI, working in teams, it is possible to sort out routine processes, create more test cases, and use obtained outcomes to reasonably distribute resources and time frames. Data mining, for example, helps in predictive analysis in order to detect risks and any possible slowdown for further action to be taken. The ability to receive constant feedback from AI reinforces the Agile testing process to thereby enable fast identification of problems, better organisational cooperation and successful implementation of intricate projects. This paper discusses the methodologies of Agile testing, a role of AI in enhancing testing efficiency, and best practices for incorporating AI in Agile engineering projects

IDENTIFICATION OF ASPECTS RELATED TO A CONTINUOUS IMPROVEMENT PROJECT

This review presents the monograph ‘’Identification of aspects related to a continuous improvement project’’, written by Mariana Roque Tognetti, published by the Course Conclusion Work or Dissertation or Thesis presented to the Faculdade de Gestão e Negócios da Universidade Federal de Uber-lândia as partial requirement for obtaining the title of Bachelor in Administration. The monograph presented by the author seeks to present a comprehensive review of the existing literature on the subject, as well as a detailed case study of a specific company. From the notes revealed in the monograph, we realize that it is important for an organization to implement tools and methods that help them identify and solve both internal and external problems. As mentioned by the author, gaps were identified in the company that was used for the field research. The author believes that the method used caused impacts on the organization, and observed that the external aspects were also present, taking into consideration how much the team was impacted by the implemented project.

Blood culture contamination in a tertiary care hospital: a retrospective three-year study

BackgroundBloodstream infections (BSI) are a leading cause of morbidity and mortality in hospitalized patients worldwide. A blood culture is the primary tool for determining whether a patient has BSI and requires antimicrobial therapy, but it can result in an inappropriate outcome if the isolated microorganisms are deemed contaminants from the skin. Despite the development of medical equipment and technology, there is still a percentage of blood culture contamination. The aims of this study were to detect the blood culture contamination (BCC) rate in a tertiary care hospital in Palestine and to identify the departments with the highest rates along with the microorganisms isolated from the contaminated blood samples.MethodBlood cultures that were taken at An-Najah National University Hospital between January 2019 and December 2021 were evaluated retrospectively. Positive blood cultures were classified as either true positives or false positives based on laboratory results and clinical pictures. Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS) version 21. A p-value of less than 0.05 was considered statistically significant for all analyses.ResultsOut of 10,930 blood cultures performed in the microbiology laboratory from 2019 to 2021, 1479 (13.6%) were identified as positive blood cultures that showed microbial growth. Of these, 453 were blood culture contaminations, representing 4.17% of total blood cultures and 30.63% of the positive blood culture samples. The highest rate of contamination was in the hemodialysis unit (26.49%), followed by the emergency department (15.89%). Staphylococcus epidermidis was the most prevalent (49.2%), followed by Staphylococcus hominis (20.8%) and Staphylococcus haemolyticus (13.2%). The highest annual contamination rate was observed in 2019 (4.78%) followed by 2020 (3.95%) and the lowest was in 2021 (3.79%). The rate of BCC was decreasing, although it did not reach statistically significant levels (P value = 0.085).ConclusionThe rate of BCC is higher than recommended. The rates of BCC are different in different wards and over time. Continuous monitoring and performance improvement projects are needed to minimize blood culture contamination and unnecessary antibiotic use.

Joint optimization of low-carbon product family configuration and smart production line selection

To meet the requirements of small batch orders and rapid production, many enterprises began to use robots, artificial intelligence, cloud computing, and other new technologies to construct smart production lines, which are high-flexible and capable of autonomously diagnosing their health and autonomously designing continuous improvement projects. In this study, a joint optimization model is established for concurrently determining the optimal product family configuration and the optimal construction plan for a smart production line. Greenhouse gas emissions are considered in the joint optimization model to realize the low-carbon design concept. A quantum evolutionary algorithm and a genetic algorithm are developed to solve the established optimization model. A case study of the electronic dictionary product family is provided to illustrate the proposed method. The numeric experiments show that the proposed model can reap more profit from a systematic perspective compared with the traditional two-stage approach, and the proposed quantum evolutionary algorithm has a good performance in solving the joint optimization problem.

Excellence via Strategic Experiential Learning (ExSEL): A Continuous Improvement Project for Developing Clinical Reasoning and Management

BackgroundThis improvement project explored using virtual patient simulations to increase an AGANCP students’ confidence applying clinical decision-making skills. MethodsA statistical analysis compared students clinical reasoning, clinical. management, and confidence scores between clinical courses with differing pedagogies focused on case-based learning versus traditional didactics. ResultsStudents showed higher clinical reasoning scores with a virtual-patient case-base pedagogy, and higher clinical management scores using traditional didactics. Higher clinical confidence scores were more frequent within the case-based approach than the traditional pedagogy. ConclusionA well-structured educational strategy using virtual-patient cases showed effectiveness in gaining competence and confidence learning clinical decision-making.

Continuous improvement project to promote evidence-based care to patients with dysphagia

Continuous improvement project to promote evidence-based care to patients with dysphagia

Utilizing a Paper Simulation to Evaluate Scheduling Workflow

<h3>Purpose/Objective(s)</h3> Increased demand for Gamma Knife (GK) radiosurgery treatment necessitated the installation of a second treatment machine to continue providing lifesaving treatment in a timely manner. The addition of a second machine brought with it the potential to double treatment volume, but the department was unable to allocate additional pre and post procedural space. Workflow and scheduling of patients was evaluated to ensure streamlined operations during the rollout of the additional machine. The objective of the Continuous Improvement (CI) project was to minimize the incidence of treatments surpassing 6:00 PM. <h3>Materials/Methods</h3> A cross functional team (represented by nursing, radiation therapists, radiation oncologists, surgeons, and physicists) employed A3 methodology to develop a current state process map for the different treatment modalities used in GK. Using the process map, the team constructed a proposed scheduling guideline that accounted for an increased patient volume without additional pre/post procedural space. Data were collected from the Brain Tumor Institute database for 325 patients regarding procedure type and duration, patient zip code, and number of days surpassing 6:00 PM. This information was used to develop a GK sample patient population. The CI process involved creating a visual representation to convey patient flow through the GK department using a poster board and patient tokens. Procedure times were generated by a randomized normal distribution of the GK sample population, and used in scenarios of varying capacity, complexity, and timing of pre-procedure imaging. The simulation included having the team complete a pre-planning huddle to determine the flow of the day that included patient order and arrival times. The simulation progressed patients through the day in 30-minute intervals while generating randomized unplanned delays formulated from clinician feedback. <h3>Results</h3> The proposed scheduling guideline was simulated at 60% capacity with mild complexity and 50% of imaging completed prior to the treatment day. A subsequent simulation was conducted at 100% capacity with moderate complexity and no imaging completed prior. This resulted in five modifications to the guideline and both simulations completing prior to 6:00 PM. Following the go-live, the number of patients treated in GK increased from 113 in 2021 to 157 in 2022 between January 1^st and February 24^th. The number of days that treatments surpassed 6:00 PM during the respective time periods reduced from 4 to 2, representing a 50% year over year reduction, despite a volume increase of 39%. <h3>Conclusion</h3> Utilization of a simulation activity to evaluate a proposed scheduling guideline provided a tangible experience with optimizing workflow and efficiency. This allowed the CI team to gain a practical understanding of the impacts of adding a second treatment machine prior to the new machine's implementation.

Internal Logistics Process Improvement using PDCA: A Case Study in the Automotive Sector

Abstract Background: The Plan-do-check-act (PDCA) cycle methodology for a continuous improvement project implementation aims for the internal logistics upgrade, which is especially important in the industrial context of a component manufacturing company for the automotive sector. Objectives: The goal is to quantify the gains from waste reduction based on the usage of the PDCA cycle as a tool in the implementation and optimisation of a milk run in an assembly line of a company in the automotive sector by determining the optimal cycle time of supply and the standardisation of the logistic supply process and the materials’ flow. Methods/Approach: The research was conducted through observation and data collection in loco, involving two main phases: planning and implementation. According to the phases of the PDCA cycle, the process was analysed, and tools such as the SIPOC matrix, process stratification, 5S, and visual management were implemented. Results: Using Lean tools, it was possible to reduce waste by establishing concise flows and defining a supply pattern, which resulted in a reduction of movements. The transportation waste was reduced by fixing the position of more than half of the materials in the logistic trailers. The developed Excel simulator provided the logistic train’s optimal cycle time. Conclusions: The assembly line supplied by milk-run was fundamental to highlight a range of improvements in the process of internal supply, such as better integration of stock management systems, greater application of quality, or the adoption of better communication systems between the different areas and employees.

Recreational activity leading to academic interest: A qualitative-narrative study

The effect of pandemic goes beyond inadequacy of acquisition of competency especially in modular distance learning, to non-attendance to school and non-enrolment in school. With the release of DepEd Order No. 34 series of 2022, the start of 5-day classes in all public schools nationwide has become a way of inviting learners who failed to enroll last school year because of non-readiness for distance learning become heightened. With this return of face-to-face interaction, recreation activity for kids last vacation before the start of school year 2022-2023 has become one way of increasing learners interest in social interaction. Lumban Central Elementary School took the opportunity to encourage the participation of intermediate learners, especially those who were out-of-school last year, in a badminton training organized by Lumban Badminton Club. This study focused on narrating the journey of the learners who joined a specific type of recreational activity (badminton training) and their interest in coming back to school. The reason for the establishment of the sports club was detailed in this paper, the three-week program provided to them from orientation to graduation, and the impact of the recreation activity to the learners as evidenced by their enrolment this school year and their continuing study at present. This qualitative, narrative research highlights the importance of recreational activities like sports in heightening the desire of children to socialize, and that includes participation in academic activities which will boost their confidence to achieve something in life. A program of instituting recreational activity for learners with their family was laid down in this study, as the school can implement family day in school compound or in the community this school year or in the coming years as the pandemic totally subsides. Day-to-day teaching episodes is also suggested as continuous improvement project. Recommendation to teachers, school heads, parents and community, high officials and future researchers were laid down at the end of the study.

The Effect of Green Human Capital, Green Structural Capital and Green Relation Capital on Company Sustainability by Mediating Green Environment Management

This study will dissect the influence of green human resources and capital on corporate stewardship by managing green environmental administration. The participants in this study were workers at PERTAMINA’s Rewul, Fuel Terminal, with a complete sample of 125 representatives. The data testing strategy uses the Structural Equation Model Partial Least Square. The results of this study found that green human resources and green social capital significantly affect the carrying capacity of the company, eirectly by intervening in the administration of the green environment; besides that, green environmental governance also has a significant impact on the sustainability of the company. On the other hand, green structural capital does not directly affect company sustainability but becomes a substantial effect by mediating green environmental management. In order to maintain sustainability, continuous improvement projects are carried out to support green innovation in implementing green technology in resource utilization and preserving the environment while still involving external parties. The company is committed to implementing the highest occupational health and safety standards, respecting and affecting the surrounding community to promote sustainable social and economic development.&#x0D; &#x0D; Received: 31 January 2022 / Accepted: 20 August 2022 / Published: 2 September 2022

Improving Vitamin D Screening in a Pediatric Rheumatology Clinic Using Structured Quality Improvement Process.

Monitoring levels of 25-hydroxyvitamin D (25-OHD) is an integral part of bone health assessment in the general pediatric population, especially in at-risk populations such as children with juvenile idiopathic arthritis (JIA), childhood-onset systemic lupus erythematosus (c-SLE), and juvenile dermatomyositis (JDM). However, only 38% of the patients with JIA, c-SLE, and JDM receiving care at Nationwide Children's Hospital Rheumatology clinic in 2016 had a 25-OHD level ordered in the preceding year. The objective of this project was to increase the percentage of 25-OHD levels ordered in patients with JIA, c-SLE, and JDM from 38% to 80% in 11 months and sustain it for 6 months. A multidisciplinary team initiated a continuous improvement project utilizing the Lean Six Sigma methodology. The team diagrammed the clinical process and identified steps that needed improvement. In addition, the team completed a root cause analysis of the process and brainstormed subsequent countermeasures. The team did not meet the 80% target but did order a 25-OHD level on 61% of patients by the end of the study period compared to 38% at the start of the study (P value 0.001). The level was sustained after the study period, with 68% of these children having a 25-OHD level ordered. The team successfully improved the screening processes for vitamin D deficiency in a busy subspecialty clinic setting using Lean Six Sigma methodology.

A Non-Invasive Method to Evaluate Fuzzy Process Capability Indices via Coupled Applications of Artificial Neural Networks and the Placket–Burman DOE

The capability analysis of a process against requirements is often an instrument of change. The traditional and fuzzy process capability approaches are the most useful statistical techniques for determining the intrinsic spread of a controlled process for establishing realistic specifications and use for comparative processes. In the industry, the traditional approach is the most commonly used instrument to assess the impact of continuous improvement projects. However, these methods used to evaluate process capability indices could give misleading results because the dataset employed corresponds to the final product/service measures. This paper reviews an alternative procedure to assess the fuzzy process capability indices based on the statistical methodology involved in the modeling and design of experiments. Firstly, a model with reasonable accuracy is developed using a neural network approach. This model is embedded in a graphic user interface (GUI). Using the GUI, an experimental design is carried out, first to know the membership function of the process variability and then include this variability in the model. Again, an experimental design identifies the improved operating conditions for the significative independent variables. A new dataset is generated with these operating conditions, including the minimum error reached for each independent variable. Finally, the GUI is used to get a new prediction for the response variable. The fuzzy process capability indices are determined using the triangular membership function and the predicted response values. The feasibility of the proposed method was validated using a random data set corresponding to the basis weight of a papermaking process. The results indicate that the proposed method provides a better overview of the process performance, showing its true potential. The proposed method can be considered non-invasive.

Critical thinking, dynamic capabilities, and project performance: empirical evidence in the continuous improvement project domain

Most continuous improvement (CI) initiatives fail, and most proposals discovering critical success factors of CI focus on the organisational level. There is little empirical evidence supporting these factors at the CI project level. Moreover, current suggestions do not show a dominant set of factors influencing the performance of the CI project. This study empirically investigates the relationships between critical thinking (CT), dynamic capabilities (DC), and project performance (PP) in the CI project domain. The sample consists of 64 projects (unit of analysis), one per organisation. We use PLS-SEM in R and control organisational factors (a binary variable representing top management commitment to the CI project). CT is positively related to DC, and DC is positively related to PP. Unlike previous works, our model focuses not on traditional ‘soft’ organisational factors or ‘hard’ project factors but cognitive factors (CT) and higher-order routines (DC) at the project level. This study extends the current explanation of why CI projects fail or succeed by incorporating CT (of the project team member) as an indirect antecedent of PP through the development of DC of the CI project. Managers and researchers on quality/project/operations management can find valuable insights in this paper to favour future CI initiatives.

A measurement model of dynamic capabilities of the continuous improvement project and its role in the renewal of the company’s products/services

A measurement model of dynamic capabilities of the continuous improvement project and its role in the renewal of the company’s products/services