Define, Measure, Analyze, Improve, Control Research Articles

Combining Lean Six Sigma and agile approach to optimize order management: action research in a Brazilian company

Purpose This paper aims to assess the combined application of Lean Six Sigma and agile approach for optimizing operational processes of order management in the seed industry. Design/methodology/approach This study is based on an action research case conducted in a multinational Brazilian Seeds Business enterprise. This paper reports on the application of the Lean Six Sigma define-measure-analyze-improve-control (DMAIC), using the steps of DMAIC cycle as a sprint of agile approach. The methodology involves outlining an operational process through sequential activities, each associated with a cycle time, equivalent number of full-time employee and number of orders. Performance metrics for the order management process include continuous monitoring of these activities, using monitoring systems, management software and manual records to collect data. Findings The findings reveal significant improvements in critical-to-quality measures related to customer care, planning and logistics. The implementation of the DMAIC methodology and agile approach resulted in tangible enhancements in cycle time, defects per opportunities and overall process efficiency. The results allow the classification of defects, the identification of their causes and, consequently, the presentation of a control plan to mitigate these problems. Furthermore, the study identifies key causes of operational issues and proposes a prioritized action plan. Research limitations/implications The limitation of this research is its restriction to a single case. The external validity of the results and generalizability to other organizational contexts may be compromised due to the lack of case diversity. The fact that the research focuses on a single company, even if it is a large multinational company, may limit the applicability of the findings to different sectors, sizes and organizational structures, which may be an opportunity for future research. Practical implications The findings suggest that the integrated approach of DMAIC and agile methodology contributes to a culture of continuous improvement and operational efficiency. The systematic collection and analysis of data enhance evidence-based decision-making, providing a robust foundation for strategic and operational choices. Moreover, the successful integration of methodologies presents a comprehensive framework applicable to diverse organizational challenges. Originality/value The paper applies action research to understand and address operational challenges, emphasizing practical solutions. The integration of DMAIC and agile enhances the depth of process analysis, enabling the identification, implementation and control of improvements. This study offers a significant contribution both to practitioners, providing practical implications, and to academics, enriching the Lean Six Sigma and agile body of knowledge.

Enhancing Fuel Ratio Efficiency for Sustainable Operations in Pit KX Mining: DMAIC Methodology

PT ABC is one of Indonesia’s largest coal mining businesses, and the mining. Pit KX is one of the company’s pits worked by contractors, and it has been mined since 2008. According to the company’s historical data from January 2022 to June 2023, overburden and coal production from Pit KX has decreased while fuel consumption has grown. Fuel is a major cost component in mining operations. The overall fuel cost represents around 35% of the company’s total operational cost. This study investigates the use of the DMAIC (Define, Measure, Analyze, Improve, Control) approach as a systematic framework for improving fuel ratio efficiency and promoting sustainable practices in pit KX mining operations. The DMAIC technique provides a disciplined pathway for discovering, assessing, and eliminating fuel-related inefficiencies. DMAIC offers a disciplined framework for improvement. By implementing DMAIC methodology, it can systematically identify and address inefficiencies in fuel utilization leading to reduced operational costs, minimized environmental impact, and enhanced sustainability of pit KX mining operations.

Implementasi Metode Six Sigma dengan Pendekatan DMAIC untuk Meminimalisasi Kecacatan Produk Pancong Pocong UMKM Ketintang

SME’s Pancong Pocong Ketintang, an SME’s in Surabaya, is currently facing problems with its products and packaging. Packaging is often not tight and breaks easily, causing the topping to overflow and the packaging to become dirty. To reduce packaging defects, the Six Sigma method with the DMAIC (Define, Measure, Analyze, Improve, Control) approach is used. This method is effective in reducing defects and improving quality. The result of this research is that the researcher defines the types of defects that exist and determines critical to quality. In the measurement stage, the average DPMO value is 157,088, which means it has a sigma level of 2.51. At the analyze stage, the results obtained from the Pareto diagram showed that the most dominant type of defect was overflowing packaging, amounting to 48%. In the improvement stage, improvements are made using the kaizen five m checklist tool which consists of man, material, method and environment. The final stage, the improvement control provided can be implemented on an ongoing basis by implementing operational standards.

Lean six sigma 4.0 methodology for optimizing occupational exams in operations management

PurposeThis paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.Design/methodology/approachThis study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.FindingsThe results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.Research limitations/implicationsIt is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.Practical implicationsThe practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.Originality/valueThis study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.

The performance analysis using Six Sigma DMAIC and integrated MCDM approach: A case study for microlens process in Vietnam

The define-measure-analyze-improve-control (DMAIC) cycle is used by the author in the context of this project to conduct research on optimizing production procedures at a business that manufactures optical components, mainly focusing on visual defects. The DMAIC cycle and techniques for quality control like Pareto charts, and experimental design and MCDM are used in this project's research to lower the error rate in the production process. Multiple criteria decision-making (MCDM) is utilized during the analysis phase of the DMAIC process to aggregate the insights of specialists and attain a more comprehensive understanding of the factors that substantially impact and contribute to microlens manufacturing defects. This enhances the Six Sigma process's agility and dependability. Microlens product is specifically the research object. After applying the DMAIC cycle, the two primary defects identified were contamination and not polishing S1. Implementing the suggested steam ratio and packaging modifications led to a noticeable enhancement. The reasonable daily product rate increased from 69 % to 79 %, saving $1932,367 annually.

Improved outcomes and cost savings for patients with bleeding disorders: a quality improvement project

BackgroundProviding optimal care for patients with bleeding disorders according to national standards remains a challenge at designated Hemophilia Treatment Centers (HTCs). Improved care may reduce bleeds and costs. ObjectivesTo improve care and demonstrate cost savings by 1) reducing preventable hospitalizations and emergency room visits (PHER) for bleeding, 2) increasing use of prophylaxis in severe hemophilia, and 3) improving patient-HTC communication and primary care engagement. MethodsProspective quality improvement project using the Define, Measure, Analyze, Improve, and Control methodology to implement uniform guideline-based bleeding disorder care at a rural HTC (N = 88). Intervention used a standardized physician checklist, improved communication, and reserved physician time for urgent management. Outcomes were determined by retrospective chart review; urgent management was tracked prospectively. ResultsIntervention significantly reduced PHER by 85.4%. Use of prophylaxis in persons with severe hemophilia increased from 58.8% to 100%; attainment of a primary care physician and electronic portal enrollment met outcomes for intervention success. HTC clinic visit attendance was low at 55.2%. The majority of patients (71.6%) had at least 1 outpatient urgent episode (mean, 0.72 episode per year), and 93% had nonurgent management (mean, 9.3 episodes per year) occurring outside of a clinic visit. Hospital PHER factor cost in the group was reduced by 94.5%, from $11,800 to $640 per patient per year—a cost savings of $982,088 yearly. ConclusionThis collaborative study shows that implementation of a carefully designed quality improvement project, such as uniform guidelines with focus on strengthening ambulatory management, led to improved outcomes and cost savings.

The application of six sigma to improve textile factory inventory costs

In the textile industry, the inventory management is pivotal for sustained success in a competitive business environment. This research, informed by an investigation into data from previous research conducted in textile factories, systematically explores the application of Six Sigma principles to address challenges in inventory management. The study utilizes the Define, Measure, Analyse, Improve, Control (DMAIC) framework to investigate and enhance inventory practices. Initiating with the Define phase, the research articulates existing issues through the project charter, setting the stage for the subsequent phases. In the Measure phase, Pareto analysis identifies key contributors to the inventory costs, including materials such as "Cotton 1/30" and "Cotton 1/24," which collectively constitute 75% of inventory costs. It is noteworthy that these materials are crucial components used in production processes, as revealed by insights from the previous research. This important discovery forms the basis for the Enhancement phase, in which the research strategically applies a Just In Time (JIT) system, resulting in a 50% reduction in the level of inventory for "Cotton 1/30" and a 70% reduction for "Cotton 1/24". Two Production Withdrawal Kanban cards as well as seven Production Instruction Kanban cards for "Cotton 1/30" and "Cotton 1/24" are required for the execution. This strategic shift aligns with market demand and results in a significant 55% decrease in holding costs.

IMPLEMENTASI LEAN SIX SIGMA UNTUK MENURUNKAN VARIASI DAN WAKTU PROSES PENGADAAN OBAT DI INSTALASI FARMASI RUMAH SAKIT ISLAM AMAL SEHAT SRAGEN

Background: Drug management needs to be done to prevent stock out, over stock, and drug purchases due to emergency conditions. Reports of drug management problems at Amal Sehat Sragen Hospital are stock outs resulting in immediate drug purchases and patients do not get the drug as they should. Lean Six Sigma combines two methodologies to help speed up certain processes so they can solve problems faster while creating more value for customers. When combined, these create a powerful methodology for managing a business and completing tasks on time, on budget, saving money, adding value and increasing productivity.
 Objectives: Assessing the implementation of Lean Six Sigma to reduce variation and processing time for drug procurement at the Pharmacy Installation of Amal Sehat Sragen Hospital.
 Methods: The method used in this study is a mixed methods with a Participatory Action Research (PAR) approach.
 Results: The results of the sample data that has variations and processing time are correlated with criticality, cost, and performance values to obtain Importance Index (II) values. Calculation of Importance Index (II), before implementation, 3 items with high Importance Index (II) values were obtained, namely "Gabapentin 300mg" (8.7), "Metformin 500mg (11.8), and "Lisinopril 5mg" (10.7) which decreased after implementation to “Gabapentin 300mg” (4.5), “Metformin 500mg (3.2), and “Lisinopril 5mg” (5.3). Assessment of the effectiveness and efficiency of drug procurement by measuring the lead time in cycle I was 9 days 23 hours 25 minutes, decreasing to 4 days 7 hours 50 minutes in cycle III. The efficiency measure based on the Value-added ratio (VAR) in cycle I was 14% and increased to 34% in cycle III.
 Conclusions: The implementation of Lean Six Sigma with DMAIC (Define, Measure, Analyze, Improve, Control) and Participatory Action Research approaches (three cycles) was able to reduce variations in the drug procurement process (critical criteria, performance, and cost) and overall lead time in the drug procurement process at Amal Sehat Sragen Hospital.

Development of a flipped learning course to deliver and scale molecular variant evaluation education: A quality improvement initiative.

Over the past several decades, molecular genetic testing volumes have grown and testing has expanded from single-gene assays to multigene panels, exome sequencing, and genome sequencing. The number of molecular genetic variants that require manual interpretation has grown simultaneously, resulting in an increased demand for education on molecular variant evaluation (MVE). To meet this growing need, a team of genetic counselors and educational experts undertook a quality improvement (QI) initiative with the objectives of assessing, standardizing, and scaling access to MVE education, without increasing instructor time to deliver the education. Using the Six Sigma define-measure-analyze-improve-control (DMAIC) framework, a flipped learning course with a series of standardized online modules was developed to deliver MVE education in an enduring and accessible format for a diverse group of learners. Outcome measures included the number of online modules developed, the number of individual learners and unique learner groups accessing MVE education, and direct instruction time required to deliver MVE education. Countermeasures to ensure maintenance of educational quality included post-course learner satisfaction scores and performance on competency assessments. Both the total number of learners and the number of unique learner groups accessing MVE education increased, while instructor time required to deliver content per learner decreased. Learner satisfaction scores remained constant and performance on competency assessments improved. The QI initiative successfully scaled MVE education to a diverse group of learners without decreasing learner outcomes or satisfaction. The flipped learning format provides a scalable and flexible educational model for instructors and learners in a rapidly changing environment that often includes remote work and education.

Pallet drop-size optimisation and its effect on the supply chain using a cost-to-serve model

The study explores the critical role of transportation within the Supply Chain, emphasising efficient planning, implementation, and control of goods and information flow from suppliers to customers. Focused on optimising the number of pallets per shipment and occurrence of the shipments to decrease secondary transport costs and environmental impact. The study is conducted with a leading Fast Moving Consumer Goods (FMCG) company in the UK by deploying the methods; Define, Measure, Analyse, Improve, Control (DMAIC) for data collection and Cost-to-Serve (CTS) for data analysis. Initially, a new Cost-to-Serve tool is developed to visualise customer performance and identify opportunities for improvement. Subsequently, a secondary tool is created to monitor the performance of identified customers. An Excel simulator is constructed to extract key performance indicators for logistics performance. Results reveal significant cost savings, with £207 K saved in the first five months of 2023 through shipment reduction of 9.09% compared to 2022. Even with inflation, the cost per pallet has remained steady, showing minimal variation from the average of 2022. This underlines the efficacy of the CTS tool in enhancing secondary transportation performance within the wider supply chain context.

APPLYING SIX SIGMA TO IMPROVE THE DEFECT RATE OF ELECTRONIC COMPONENTS: A SIX SIGMA CASE STUDY

This study aimed to improve the touch responses of electronic products. The improvement method was based on six sigma improvement steps. Product quality was improved using define, measure, analyse, improve, control (DMAIC) and statistical quality control methods to reduce the cost and waste of defective products. The project identified five critical processes from the manufacturing process and eight critical to characteristics (CTCs). Then CTCs were identified through the critical to characteristic diagram. The root causes were verified using the experimental plan method, scatter diagram, and double ratio test. This study identified three root causes, namely ‘poor reed touch value’, ‘base cavity width’, and ‘jig precision’. The last two causes were evaluated, and countermeasures were taken to ‘change the size of the base cavity’, ‘change the design of the assembly jig’, and ‘change the process of the assembly jig’. The target rate of the overall product defect rate reached 127%.

Reduction in Average Length-of-Stay in Emergency Department of a Low-Income Country's Cancer Hospital.

Prolonged length of stay (LOS) in emergency departments (ED) is a widespread problem in every hospital around the globe. Multiple factors cause it and can have a negative impact on the quality of care provided to the patients and the patient satisfaction rates. This project aimed to ensure that the average LOS of patients in a tertiary care cancer hospital stays below 3 hours. The Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) approach was followed. The average LOS was 166 minutes before implementing interventions. The two primary reasons for the increased length of stay were delays secondary to physician assessment and diagnostic lab reports. Strategies were defined to control these factors, which helped reduce the average length of stay to 142 minutes, a 30% reduction. A process improvement model similar to this project is recommended to enhance the quality of hospital services. It will provide valuable insights into the process flow and assist in gathering precise data on the various steps involved. The data collected can then be analyzed to identify potential causes and make informed decisions that can significantly improve hospital processes.

Utilising a hybrid DMAIC/TAM model to optimise annual maintenance shutdown performance in the dairy industry: a case study

PurposeOutput from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.Design/methodology/approachCombining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.FindingsApplication of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.Practical implicationsThe results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.Originality/valueTo the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

ANALYSIS OF LEAN SIGMA - DMAIC IMPLEMENTATION WITH ENVIROMENTAL CONSIDERATIONS IN OIL & GAS INDUSTRY (CASE STUDY: ONSHORE FIELD ABC TERMINAL FIELD – PT XYZ)

The oil and gas industry is facing increasing pressure from an operations and environmental compliance perspective. The adoption of Lean Sigma methodology has been shown to improve the operational performance of various industries, including the Oil and Gas industry. The objective of this research is to analyse the implementation of a sustainable improvement framework based on the Lean Sigma DMAIC (define-measure-analyse-improve-control) method, considering the environment in maintaining sustainable business in the oil and gas industry. The research action approach in a case study is used to illustrate the application of the proposed Lean Sigma - DMAIC framework to improve operational performance and the environment in the oil and gas industry. The case study illustrates the application of the Lean Sigma - DMAIC cycle to improve crude oil quality – Base sedimen & water (BS&W) product and optimize energy consumption in the processing of crude oil. After improving the quality of oil production that previously experienced deviations and making improvements and efficiencies in the processing plant, this oil processing plant can achieve operational cost savings of US$ 181,847.95 and environmental benefits in reducing CO2 emissions by 1,685.81 tons (CO2 eq) by reducing the gas consumption used to heat crude oil in the oil treating plant.

Integrated Lean Six Sigma and Kotter change management framework for emergency healthcare services in Saudi Arabia

PurposeLean Six Sigma (LSS) implementation follows a structured approach called define-measure-analyze-improve-control (DMAIC). Earlier research about its application in emergency healthcare services shows that it requires organizational transformation, which many healthcare setups find difficult. The Kotter change management model facilitates organizational transformation but has not been attempted in LSS settings till now. This study aims to integrate the LSS framework with the Kotter change management model to come up with an integrated framework that will facilitate LSS deployment in emergency health services.Design/methodology/approachTwo-stage Delphi method was conducted by using a literature review. First, the success factors and barriers of LSS are investigated, especially from an emergency healthcare point of view. The features and benefits of Kotter's change management models are then reviewed. Subsequently, they are integrated to form a framework specific to LSS deployment in an emergency healthcare set-up. The elements of this framework are analyzed using expert opinion ratings. A new framework for LSS deployment in emergency healthcare has been developed, which can prevent failures due to challenges faced by organizations in overcoming resistance to changes.FindingsThe eight steps of the Kotter model such as establishing a sense of urgency, forming a powerful guiding coalition, creating a vision, communicating the vision, empowering others to act on the vision, planning for and creating short-term wins, consolidating improvements and producing still more change, institutionalizing new approaches are derived from the eight common errors that managers make while implementing change in the institution. The study integrated LSS principles and Kotter’s change management model to apply in emergency care units in order to reduce waste and raise the level of service quality provided by healthcare companies.Research limitations/implicationsThe present study could contribute knowledge to the literature by providing a framework to integrate lean management and Kotter's change management model for the emergency care unit of the healthcare organization. This framework guides decision-makers and organizations as proper strategies are required for applying lean management practices in any system.Originality/valueThe proposed framework is unique and no other study has prescribed any integrated framework for LSS implementation in emergency healthcare that overcomes resistance to change.

Using DMAIC for in-plant logistic activities improvement

Goal: In-plant logistics activities are important for increasing the performance of the supply chains, so our research aims to study the application of Six Sigma tools for in-plant logistics activities in the cement industry. Our research contributes to the literature by developing a real case study that provides insights into the practical implementation of continuous improvement programs. Design / Methodology / Approach: This study uses the Industrial Case Study in a large cement plant, a branch of a multinational business group, in Brazil’s Middle-west region. This research applies Define, Measure, Analyze, Improve, Control (DMAIC) guidelines with Statistical Process Control tools for solving a real problem for out-control processes. From this, we propose an improvement plan to correct flaws in the in-plant cement loading and unloading process (in-plant logistics). Results: The results suggest that based on the control chart, the studied in-plant logistics activities were out of control. These processes exhibit a high variability, between 3σ and 5σ, presenting 26 problems with causes related to machine, measure, and human resources. An out-control action plan was proposed aiming for improvements to solve these problems. Limitations of the investigation: On the out-control action plan, this study presents an improvement proposal. The action plan does not fully develop the control step for DMAIC. Practical implications: Managers in the cement industry can use our case for insights and learning about improvement programs, especially for the in-plant logistics activities addressing processing-based manufacturing environments. Originality / Value: Our research contributes a real case study that applies the DMAIC methodology, with a specific focus on in-plant logistics activities. By developing the application of improvement programs within the cement industry, our study offers practical insights into how processing industries can effectively implement such programs.

Sustainable Lean Six-sigma: A new framework for improve sustainable manufacturing performance

Sustainable Manufacturing is essential in supporting a more sustainable production process in the current era. However, continuous improvement research that utilizes Manufacturing Sustainability Index (MSI) scores in improving Sustainable Manufacturing performance is still limited. Therefore, this study aims to propose a new framework for evaluating Manufacturing Sustainability based on lean Six Sigma and Sustainable Manufacturing concepts using Sustainable Value Stream Mapping (Sus-VSM). We call this new framework Sustainable Lean Six-sigma (SLSS) based on the DMAIC (Define, Measure, Analyze, Improve, Control) approach. The SIPOC diagram and the Delphi method are used in the Define stage to select relevant indicators. Then, the selected indicators were evaluated in the Measure stage, and the Manufacturing Sustainability Index (MSI) was calculated. At the Analyze stage, the Sus-VSM is analyzed. At the Improve stage, improvement proposals are made using Failure Mode and Effect Analysis (FMEA), and a future Sus-VSM is created. Finally, in the Control stage, check sheets are created to control the implementation of the proposed improvements. In the DMAIC process, Sus-VSM is used as a production flow mapping using a traffic light system to map indicators in each process and MSI values on the production line. A case study was also conducted on the Agro-Food Industry. The results showed that the proposed framework could be implemented in the company and successfully improved the Manufacturing Sustainability Index (MSI) score from 88.78% to 93.80%. The implication of this research shows the potential of using the SLSS framework in improving manufacturing sustainability performance in industrial sectors.

Application of Lean Six Sigma Method in Hospital Management Process: Performance Optimization and Waste Reduction

In the dynamic environment of healthcare, hospital management constantly seeks methods to enhance performance and reduce inefficiencies. This study explores the implementation of the Lean Six Sigma (LSS) methodology in hospital management to optimize performance and minimize waste. Lean Six Sigma, a combination of Lean management and Six Sigma, is renowned for its systematic, data-driven approach in improving process efficiency and quality. We conducted a comprehensive analysis in a tertiary care hospital, employing LSS tools such as DMAIC (Define, Measure, Analyze, Improve, Control) framework, value stream mapping, and root cause analysis. The study focused on critical areas such as patient flow, inventory management, and operational processes. Our findings reveal significant improvements in patient wait times, reduction in inventory costs, and enhanced operational efficiency. The application of LSS led to a more patient-centric approach, streamlined processes, and a culture of continuous improvement within the hospital. This research contributes to the growing body of knowledge on LSS in healthcare and provides a practical framework for hospital administrators seeking to implement efficiency-enhancing strategies.

Abstract 18105: Lean Six Sigma Approach to Improve Post Percutaneous Coronary Intervention Cardiac Rehab Referral Rates

Background: Cardiac rehabilitation referral rates remain low despite known benefits including decreased mortality and improved quality of life. Studies have identified factors tied to both positive and negative predictors of referral rates, however, overall, it appears to be due to site-specific variation demonstrating the need for hospital-level intervention. Aims: This quality improvement study aimed to improve cardiac rehabilitation referral rates after PCI at our institution utilizing the Lean Sigma Six (LSS) approach, which has been described as a means to improving the quality of healthcare delivery. Methods: An interdisciplinary team used the Define-Measure-Analyze-Improve-Control (DMAIC) framework to implement this study. A GEMBA walk i.e., personal observation of workflow was performed. We Define d and Measure d process of cardiac rehabilitation and the referral rates. We Analyzed to identify that the orders were being placed by multiple team members including residents, general and interventional cardiology fellows, attendings, and nurse practitioners. Process maps were created, and our Intervention was to involve interventional cardiology fellows as stakeholders best suited to place orders since they are involved in all PCIs at our institution. Education was provided specifically to them beginning in July 2022. Statistical Process Control charts were used to analyze data trends from 2019 - 2022 where a total of 3046 PCIs were performed. Control process involved reinforcing the effect of intervention in quarterly meetings. Results: Baseline referral rates ranged from 10-60%. A significant increase in cardiac rehabilitation referral rate achieving a target referral greater than 90% was observed and maintained through the subsequent quarters. Conclusion: LSS is a powerful methodology to examine causes of delay in care. Intervention using LSS principles and tools, may help improve system processes to achieve desired quality outcomes.

A Data-driven Framework to Reduce Diesel Spillages in Underground Mines

Several methodologies have been developed to manage diesel in open-cast mining due to its high demand and increasing diesel prices. Although the use of diesel-powered equipment in underground mines has increased over the years, effective management thereof has not received the same attention. With the advent of Industry 4.0, data can be utilised more effectively by modern businesses to identify and solve problems in a structured manner. In this study, an underground mine was used as a case study to determine whether a Data, Information, Knowledge, Wisdom (DIKW) method for diesel management could be coupled with the Six Sigma Define, Measure, Analyse, Improve, Control (DMAIC) tool to make more informed decisions and gain new insights to help reduce diesel wastage underground. The new integrated methodology identified diesel spillages and highlighted the biggest contributors to these underground spillages. The Six Sigma DMAIC domain utilised root cause analysis to determine the reason for recent systems failures, followed by the identification of practical solutions to eliminate up to 200 ML (megalitres) of diesel spillage. With this information, the case study mine stands to save over USD 175,000 per annum.