Operational Excellence: A Model Pathway to Improve Yield and Productivity of the Pharmaceutical Tablet Manufacturing Process

Presently the manufactures are facing a great pressure to reduce cost of manufacturing and provide new and quality products in the market on a regular basis. The India's manufacturing sector is striving hard towards operational excellence. Reduction of waste, improvement of quality, higher through put and overall more efficient production system is leading India towards a manufacturing revolution. A good number of companies have started implementing a range of business strategies including going lean, and using manufacturing strategies such as TPM, TQM, Six Sigma, JIT etc. to obtain operational excellence. Total Productive Maintenance (TPM) refers to a management system for optimizing the productivity of manufacturing equipment. A study to evaluate the implementation aspects and success factors of TPM initiatives taken by Indian industry for achieving manufacturing excellence is carried out and presented in this paper. There remained considerable improvement in the morale of employees, skill level of employees, technological up-gradation, machine conditions, and customer satisfaction level after TPM. Also the industries remained successful in improving their overall equipment effectiveness (OEE) up to 30% and some of them achieved the world class level of 95% OEE.

This paper presents a new metric for describing the sustainability improvements achieved, relative to the company’s initial situation, after implementing a lean and green manufacturing system. The final value of this metric is identified as the Overall Environmental Equipment Effectiveness (OEEE), which is used to analyze the evolution between two identified states of the Overall Equipment Effectiveness (OEE) and the sustainability together, and references, globally and individually, the production steps. The OEE is a known measure of equipment utilization, which includes the availability, quality and performance of each production step, In addition to these factors, the OEEE incorporates the concept of sustainability based on the calculated environmental impact of the complete product life cycle. Action research based on the different manufacturing processes of a tube fabrication company is conducted to assess the potential impact of this new indicator. The case study demonstrates the compatibility between green and lean manufacturing, using a common metric. The OEEE allows sustainability to be integrated into business decisions, and compares the environmental impact of two states, by identifying the improvements undertaken within the company’s processes.

In the face of pandemic-induced emergencies and unpredictable natural disasters, industries are compelled to implement rescue plans to mitigate unexpected risks. In this context, Overall Equipment Effectiveness (OEE) is considered as a key metric, followed by sustainability efforts to manage unforeseen risks, encompassing social, environmental, and economic aspects. OEE is considered as a lean tool to determine the efficiency of equipment or processes on par with the world class OEE standard, i.e., 85%. Performance, Availability and Quality as three main drivers of OEE. This research study explores the implementation of OEE in conjunction with sustainability principles in an auto sector manufacturing firm, aiming to enhance operational efficiency and sustainability practices. The research involves a 12-week initial session from April to June 2022, followed by an analysis of July to September 2022, resulting in an impressive OEE value of 48%. Notable improvements in Availability (89.75%), Performance (72.68%), and Quality (73.82%) contribute significantly. The analysis reveals enhancements in scrap rework (17%), training (16%), maintenance (13%), material availability (12%), and production capability (11%). Achievements include improvements in green profile (25%), health and safety (20%), and energy efficiency (25%), along with reductions in carbon dioxide emissions (21%), waste management (17%), and scrap (15%). This research underscores the commitment of the case study industry to sustainable development and economic growth, showcasing significant enhancements in product quality and efficiency. The integration of sustainability principles into OEE initiatives is pivotal for modern industrial optimization. The study results highlight the profound significance of this synergistic relationship, particularly within the blending section, driving substantial positive outcomes in manufacturing processes and operational excellence. The implementation of sustainability efforts not only mitigates risks and fosters growth for automotive manufacturers but also yields environmental benefits. Based on findings of this study, a roadmap for automotive manufacturers is devised to achieve robust OEE while concurrently reaping economic and environmental rewards by employing sustainability principles.

Industry in each country has increased, as well as industry in Indonesia which is experiencing a fairly rapid increase. The improvement of product quality is that it can be done by carrying out maintenance to the machine used by the company. Total Productive Maintenance (TPM) is a process of machine maintenance carried out in industry to maximize and can increase productivity. PT XYZ is a manufacturing company that produces chemicals used for fabric production. This study aims to measure the level of effectiveness of the equipment used in PT. XYZ and measure how effective total equipment production. Determine the causal factors of low Overall Equipment Effectiveness (OEE) value and identify losses incurred, by providing proposed improvements in the factory by applying the TPM method. OEE values obtained in reactor engines at the plant in the period January-October 2021 with an average value reached of 55.63% - 60.60% are still below the overall equipment effectiveness (OEE) standard value caused by Quality Ratio which is still below jipm standard with an average value of 98.54%. Each company can find out the effectiveness of the machine used by using calculations of the level of effectiveness of equipment using the Total Productive Maintenance (TPM) method based on overall equipment effectiveness (OEE)values. Method is used to measure the number TPM by using the Overall equipment effectiveness (OEE) method. The use of this method to provide equipment performance results and accurate calculations to determine the effective engine that will be

Industry in each country has increased, as well as industry in Indonesia which is experiencing a fairly rapid increase. The improvement of product quality is that it can be done by carrying out maintenance to the machine used by the company. Total Productive Maintenance (TPM) is a process of machine maintenance carried out in industry to maximize and can increase productivity. PT XYZ is a manufacturing company that produces chemicals used for fabric production. This study aims to measure the level of effectiveness of the equipment used in PT. XYZ and measure how effective total equipment production. Determine the causal factors of low Overall Equipment Effectiveness (OEE) value and identify losses incurred, by providing proposed improvements in the factory by applying the TPM method. OEE values obtained in reactor engines at the plant in the period January-October 2021 with an average value reached of 55.63% - 60.60% are still below the overall equipment effectiveness (OEE) standard value caused by Quality Ratio which is still below jipm standard with an average value of 98.54%. Each company can find out the effectiveness of the machine used by using calculations of the level of effectiveness of equipment using the Total Productive Maintenance (TPM) method based on overall equipment effectiveness (OEE)values. Method is used to measure the number TPM by using the Overall equipment effectiveness (OEE) method. The use of this method to provide equipment performance results and accurate calculations to determine the effective engine that will be

Nowadays, consumers expect manufacturers to provide excellent quality, reliable delivery and competitive pricing. This demands that the manufacturer's machines and processes are highly reliable. In order to possess highly reliable machines to make sure smooth manufacturing process, many organizations have implemented Total Productive Maintenance (TPM) as the enabling tool to maximize the effectiveness of equipment by setting and maintaining the optimum relationship between people and their machines. Overall Equipment Effectiveness (OEE) is used as a measure when evaluating the result of TPM. This paper intends to find out the difference between before and after the TPM implementation to OEE result. Comparison between before and after the implementation of TPM is carried out to see the difference that TPM can bring to an organization. Elements that constitute the OEE equation will be analyzed in order to identify which one that affects OEE result. After identifying, improvement will be made on that element so that OEE result will be improved ultimately. The approach used in this paper is experimental and the instruments used to collect data are observation and interview. Microsoft Excel is used to analyze data obtained and calculate OEE. Hence, TPM is a useful tool in helping firm to achieve optimal manufacturing process. By being able to achieve this level of maintenance, an organization will be able to reap competitive advantages brought by TPM, thus, producing quality products that manage to satisfy customers and subsequently generating greater profits.

Purpose Achieving operational excellence in supply chain management (SCM) is essential for enhancing customer satisfaction, improving efficiency, and sustaining industrial competitiveness. This paper aims to develop an integrated Lean Six Sigma (LSS) framework to optimize SCM by minimizing waste, enhancing process reliability and improving responsiveness. The framework’s effectiveness is validated through a case study in a spare parts manufacturing company in Egypt, demonstrating its practical application and impact. Design/methodology/approach The study identifies critical success factors (CSFs) for effective LSS implementation in SCM. A structured DMAIC (Define-Measure-Analyze-Improve-Control) approach is applied, offering a data-driven methodology for optimizing supply chain performance and ensuring sustainable improvements. Findings The proposed framework significantly enhances SCM efficiency, operational effectiveness and customer satisfaction. Key performance improvements include product quality (85%–89%), sigma level (2.5–2.7) and processing time reduction (645–370 h/ton), Overall Equipment Effectiveness (OEE) increases (75% to 81%), value-added activity enhancement (50% to 54%), and customer satisfaction growth (87% to 89%). These improvements, achieved through LSS methodologies, drive defect reduction, workflow optimization, enhanced equipment utilization and a culture of continuous improvement, ensuring long-term operational excellence. Research limitations/implications This study’s scope was limited to a single product in a specific industrial context. Future research should explore the broader applicability of the LSS-SCM framework across various sectors, including services, to assess its versatility and generalizability. Expanding the research scope will provide valuable insights into the framework’s adaptability and potential impact across different industries. Practical implications This research provides a structured and replicable methodology for managers and engineers to enhance SCM performance, streamline production processes, and strengthen operational resilience. It offers practical, data-driven strategies for integrating LSS into SCM, enabling organizations to optimize processes, reduce waste and achieve long-term competitive advantage. Originality/value This study presents a comprehensive, empirically validated LSS framework for SCM optimization. By demonstrating the structured application of LSS tools, provides a novel, systematic approach to enhancing efficiency, effectiveness and resilience in modern supply chains, fostering sustainable continuous improvement and industrial competitiveness.

For the manufacturing sectors to survive and flourish in the competitive international market, constant improvement of small and medium firms is a must. The current scenario of any manufacturing industry focuses on the quality and on-time delivery of the products to satisfy their customers. This paper is the result of a study conducted in the manufacturing industry in south India, with a particular focus on the machining of several automobile components. The study aimed to identify and eliminate bottlenecks in the production line, as well as to increase production using techniques like define, measure, analyse, improve, and control (DMAIC), SIPOC, value stream mapping, IoT-enabled coolant concentration monitoring system, and IoT-enabled tool life monitoring. The overall equipment effectiveness (OEE) for the bottleneck operation was found to be 58.74%. By implementing Lean Six Sigma tools and techniques, the quality of the product has been increased and the lead time has been reduced and as a result, the OEE was improved by 4.88%. This in turn helps in improving the overall production in the industry.KeywordsLean Six SigmaInternet of ThingsTool life monitoringValue stream mappingOEE

ABSTRACTThe study explores how digitalization together with lean manufacturing techniques influences operational performance within the apparel sector while highlighting Overall Equipment Effectiveness (OEE) as a critical indicator of performance. The apparel industry usually achieves OEE values from 40% to 60% because its labor‐intensive production and low levels of automation prevent it from reaching full productivity potential. Through targeted interventions, it is possible to increase these values to reach a sustainable benchmark of 75%. Achieving this target requires reducing downtime, addressing performance inefficiencies, and minimizing quality‐related disruptions to enhance operational stability. Case studies conducted at Company X and Company Y have identified key bottlenecks hindering optimal OEE, including low automation levels and challenges arising from the inherent flexibility requirements of apparel production. Proposed solutions include the integration of advanced process monitoring devices (PMDs), digital line balancing algorithms, and lean manufacturing techniques. These strategies collectively reduce productivity losses and support the attainment of the 75% OEE target. However, reaching the world‐class OEE benchmark of 85% is noted as a significantly challenging goal due to sector‐specific constraints. This research presents a strategic framework highlighting the synergistic potential of digitalization and lean manufacturing tools in enhancing operational efficiency. By adopting these integrated approaches, apparel manufacturers can improve their OEE performance, achieve higher productivity, and secure long‐term competitiveness in a rapidly evolving industry. Nevertheless, the study underscores that achieving 85% OEE remains a formidable challenge, given the unique limitations of the sector. Therefore, setting realistic and sustainable targets is crucial for the successful transformation of the apparel industry.

Purpose This study aims to investigate the relationship between the use of digital twin (DT) and the overall equipment effectiveness (OEE) metric from the perspective of Lean 4.0. Design/methodology/approach A systematic literature review was conducted, and the resulting articles were subjected to a content analysis based on Bardin (2011). Using spreadsheets and graphical software, the data were organised to facilitate the presentation of the results. Findings The results characterise the DT into two groups, which address the level of integration of this system: “Partial interaction” and “Full interaction”. With this distinction made, we gathered the inhibitors related to the development of full DT integration, to detail opportunities and insights from the application of Lean 4.0, enabling the migration from one system to another and allowing operational excellence through the OEE indicator. Research limitations/implications This study is limited by its theoretical approach, relying on a systematic literature review rather than empirical validation. It also highlights insights into how Lean 4.0 can be used by professionals to facilitate the transition from Partial Interaction to Full Interaction models for the integration of OEE measurements. Originality/value The novelty of this study lies in the application of Lean 4.0 to enable DT integration across production systems, filling a gap in the literature regarding the use of DT for tracking OEE as a tool to enable operational excellence.

The integration of Lean Manufacturing (LM) and Industry 4.0 (I4.0), also known as Lean Manufacturing 4.0 or Smart Factory, is increasingly adopted by manufacturers for their effectiveness in reducing losses and improving efficiency. Despite their established benefits, there is a notable gap in comprehensive analyses regarding the integration of I4.0’s Manufacturing Execution System (MES) and Total Productive Maintenance’s Overall Equipment Effectiveness (OEE) within lean practices. Therefore, the purpose of this paper is to provide a comprehensive literature review offering thorough insights into the trends, applications, and impacts of Lean Manufacturing 4.0. Utilizing a systematic literature review, this research initially assesses 250 papers for bibliometric trends, narrowing down to 44 papers for content analysis. The bibliometric analysis reveals trends in Lean Manufacturing 4.0 publications, including historical series, publications across countries, highly cited articles and types of papers. Noteworthy findings from the content analysis are the frequent connection between LM’s Process Mapping and I4.0’s MES, as well as the frequent association of I4.0’s Internet of Things with LM’s OEE. The OEE-I4.0 integration is predominantly characterized by enhanced OEE and real-time data utilization, while MES-Lean integration showcases documented impacts on production efficiency, resource management, and continuous and operational system improvement. This study highlights the importance of adopting relevant Lean Manufacturing 4.0 practices for manufacturers and scholars. The importance of Lean Manufacturing 4.0 practices and the understanding of connections between OEE and I4.0, as well as MES and LM, are addressed in this study, emphasizing the imperative for businesses to adopt Lean Manufacturing 4.0.

There is a growing need for operation management in today's manufacturing sector. It is no wonder why more and more companies are now establishing a completely separate department called 'operational excellence', which envisages potentials for implementation of techniques like lean manufacturing, six sigma, TPM(Total Preventive Maintenance), TQM(Total Quality Management), and many more. The six sigma has now become inevitable in manufacturing industries which targets quality and customer satisfaction. Six sigma concept, which took birth in Motorola back in 1980's has now forayed into numerous sectors including manufacturing, finance, logistics, healthcare etc. Implementation of six sigma in mass production is comparatively easy because of less or no product variability, however equally abstruse for job order production system. Our paper focuses on potential applications of six sigma in job order production, and we have taken up study of a turbine machining factory unit, wherein quality and precision play a pivotal role. We have also explored the prospects of combing lean manufacturing with six sigma.

Nowadays, consumers expect manufacturers to provide excellent quality, reliable delivery and competitive pricing. This demands that the manufacturer's machines and processes are highly reliable. In order to possess highly reliable machines to make sure smooth manufacturing process, many organizations have implemented Total Productive Maintenance (TPM) as the enabling tool to maximize the effectiveness of equipment. Overall Equipment Effectiveness (OEE) is used as a measure when evaluating the result of TPM. This paper has found out the difference between before and after the TPM implementation to OEE result. Comparison between before and after the implementation of TPM was carried out to see the difference that TPM can bring to an organization. Elements that constitute the OEE equation have been analyzed and indentified which one that affected OEE result. After identifying, improvement has been made on that element so that OEE result would be improved ultimately. Microsoft Excel was used to analyze data obtained and calculate OEE. Hence, TPM is a useful tool in helping firm to achieve optimal manufacturing process. By being able to achieve this level of maintenance, an organization will be able to reap competitive advantages brought by TPM, thus, producing quality products that manage to satisfy customers and subsequently generating greater profits.

Globalization and highly competitive business environment are pushing many organizations to realize numerous productivity improvement efforts in order to continue to survive. To gain competitive advantage, manufacturing organizations are compelled to adopt productivity enhancement programs such as total quality management (TQM), total productive maintenance (TPM), lean manufacturing concept to achieve operational excellence. Overall Equipment Effectiveness (OEE) is a well-accepted production performance measure to gauge the equipment effectiveness. OEE is defined as how much the equipment is performing to meet the production planned target. OEE, in manufacturing is merely a percentage figure to evaluate how effective the manufacturing equipment is utilized. OEE is not directly linked to profitability. Most companies do not associate increases or decreases in OEE to financial performance. This paper presents the relationship between OEE, production throughput and production part cost in order to express and translate OEE in monetary units.

This study evaluates the effectiveness of World Class Manufacturing (WCM) implementation in optimizing operational performance within the fibreglass insulation manufacturing sector. The study employed a systematic approach utilising Value Stream Mapping (VSM) and Overall Equipment Effectiveness (OEE) as the primary evaluation tools. Data collection was conducted from 2023 to 2024, focusing on performance, availability, and quality metrics. Results show a significant improvement in OEE from 81.3% to 87.3%, validating the effectiveness of WCM in optimizing operations. The implementation fostered a culture of operational excellence, as evidenced by improved process understanding and increased employee engagement in improvement initiatives. Pareto analysis revealed several inefficiencies, enabling targeted interventions in line with WCM’s “zero waste” philosophy. The methodology was found to be adaptable to existing production systems, suggesting its viability for manufacturing environments in emerging economies. This study contributes to the literature by providing empirical evidence of the effectiveness of WCM in driving systematic improvement and organizational change, particularly in industrial development in emerging economies. The findings support the role of WCM in establishing sustainable operational excellence frameworks capable of meeting global competitive challenges.