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The purpose of this paper is to examine how holistic improvement work can be organized and what challenges can be observed in the process of adopting a holistic perspective on production system improvement.

A qualitative case study and a questionnaire have been carried out. Data for the case study has been collected through semi-structured interviews, archived documents and participatory observations. The questionnaire was done in order to increase the generalizability of the findings from the case study and further validate the conclusions.

The improvement work at the case company is organized as a continuous improvement approach in a Lean Production system in the form of a company-specific production system (XPS), in which two other improvement approaches are incorporated. Some of the identified challenges are: the establishment of a holistic perspective on improvement opportunities; the development of a process to update the production strategy; the continuous update of the Operational Management System during the XPS implementation; aggregating measures for the improvement work and measuring the effect of improvement work.

As the current case study is limited to one case company, future research is interested in expanding to other production systems contexts for further validation.

The present study offers an increased understanding of the integration difficulties of improvement work that many production companies face regarding operational effectiveness, and based on the findings, some implications for management are presented.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

The purpose of this study is to introduce an enterprise's productivity management named “Production efficiency improvement - PEFF”. This study shows the way of developing the management system to keep their shop floor “flexible to change” and “continuously controlling and improving” from the different levels and in various factories.

This study refers to Toyota's PEFF management system in the context of productivity enhancement through detailed management processes including yearly management, monthly management, daily management and its application in a case study from another sector as a model case of PEFF expansion. The methodology of this study is to introduce a method for production efficiency analysis, measure and select standard time through PEFF calculation.

Toyota's PEFF management can be extremely effective at developing management's ability to conduct day-to-day shop-floor management, know-how sharing and how Toyota applies PEFF to develop the world-standard on manpower efficiency for their factories. Besides, this study shows the applicable of PEFF improvement has successfully conducted in other manufacturers in a flexible way to achieve the improvement targets.

The results of this study will aid the managers in production lines to find the method of calculating and evaluating production efficiency through Toyota's management techniques such as PEFF, YIP, WVACT and standard time. However, the approach for this paper was from a synchronized system as Toyota is limited to generalized to small and medium-sized enterprises.

This paper is introducing the original Toyota's management technique to sustainable enhance their manpower performance and efficiency and answer the question of why TPS still exists in the age of digital management. PEFF management serves as an example of a value management process to help manufacturers to set guidelines to improve their productivity.

The purpose of the paper is to present a fundamental mindset that an experienced Japanese Toyota Production System (TPS) consultant has when he drives a series of improvement activities during a lean transformation.

The main author of this paper conducted participant observations on two lean transformation cases at two medium‐sized Swedish manufacturing companies. The studied lean transformations are driven by the mentioned Japanese consultant. Before he became a consultant, he had practiced TPS more than 20 years at a supplier company of Toyota.

Instead of making a detailed plan to implement lean production, the consultant focuses on creating the need for improvement. The identified fundamental mindset that drives a lean transformation can be described as “occasionally by force, create a situation where people have no choice (or little choice) but to feel the need of improvement. The situation is such that it brings different problems up to surface. Through letting people solve the problems one‐by‐one, the performance of the operation as well as the capability of individual and organizational learning are improved.” Various lean techniques are simply used based on the surfaced problems.

The recent research shows that a contingent nature is required in lean transformation, especially when it requires an organizational cultural change. However, a limited number of researches have shown practical ways of conducting a lean transformation with a contingent approach. The paper identifies a simple but practical way of doing it.

The purpose of this paper is to investigate multiple criteria decision-making (MCDM) processes within a flow-line production-improvement activity. Investigation can lead to understanding of how a process improvement framework influences the decision and fulfillment of the potential to successfully change the operation process.

The improvement process selection (IPS) framework is built systematically by incorporating all related decision criteria with suitable tools required to select improvement alternatives. The process consists of three phases: identification, prediction, and selection. The IPS framework is validated through a case study of a company that was carrying out a flow-line production-improvement project.

The developed framework is used to prioritize the problem scope and select the solutions from various options. The case study illustrates the process through which the developed framework provided a systematic approach in identifying the solutions and achieving the desired performance improvement. Prediction result analysis shows the framework achieved sustainable process improvement changes and prevents management levels from higher risks in failure improvement. The feedback of the case study has verified the robustness of the framework.

Quantitative improvement tools, such as MCDM employed in the IPS framework are vital for better understanding of the improvement impact of changes. Thus, the improvement solution alternatives can be analyzed in more comprehensive ways by considering numerous performance metrics in order to select the best improvement alternatives.

The IPS framework can assist the company in determining optimal decisions in relation to selection of improvement alternatives. As a result, production performance can be affected positively.

The purpose of this paper is to review the literature on Total Productive Maintenance (TPM) and to present an overview of TPM implementation practices adopted by the manufacturing organizations. It also seeks to highlight appropriate enablers and success factors for eliminating barriers in successful TPM implementation.

The paper systematically categorizes the published literature and then analyzes and reviews it methodically.

The paper reveals the important issues in Total Productive Maintenance ranging from maintenance techniques, framework of TPM, overall equipment effectiveness (OEE), TPM implementation practices, barriers and success factors in TPM implementation, etc. The contributions of strategic TPM programmes towards improving manufacturing competencies of the organizations have also been highlighted here.

The literature on classification of Total Productive Maintenance has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of various TPM implementation practices demonstrated by manufacturing organizations globally. It also highlights the approaches suggested by various researchers and practitioners and critically evaluates the reasons behind failure of TPM programmes in the organizations. Further, the enablers and success factors for TPM implementation have also been highlighted for ensuring smooth and effective TPM implementation in the organizations.

The paper contains a comprehensive listing of publications on the field in question and their classification according to various attributes. It will be useful to researchers, maintenance professionals and others concerned with maintenance to understand the significance of TPM.

This study aims to utilize DMAIC methodology along with value stream mapping and other Lean Six Sigma tools in a major automobile light manufacturing industry to reduce defect rates and increase production capacity in their manufacturing line. The study also proposes a modified framework based on lean principles and FlexSim to identify and reduce waste in the selected industry.

A Lean Six Sigma modified framework has been deployed with DMAIC to reduce the defect rate and increase the production rate. Various tools like value stream mapping, brainstorming, Pareto charts, 5S, kanban, etc. have been used at different phases of DMAIC targeting wastes and inventory in the production line. Also, a simulation model has been utilized for the automobile light manufacturing industry to improve the machine utilization time with varying batch sizes.

The results of the study indicated a 53% reduction in defect rates. Thus, there would be an expected improvement in sigma value from 3.78 to 3.89 and a reduction in defects per million opportunities (DPMO) from 11,244 to 8,493. Additionally, simulation model using FlexSim was developed, and the optimum ordering batch size of raw material was obtained. It was also analyzed that idle time for various stations could be reduced by up to 30%.

The utilized framework helps identify defects for managers to increase production efficiency. The workers, operators and supervisors on the production line also need to be trained regularly for identifying the areas of improvement.

The modified Lean Six Sigma framework used in this study includes FlexSim simulation to make the framework robust, which has not been used with LSS tools in the literature studied. Also, the LSS finds very less application in the manufacturing domain, considering which this study tends to add value in existing literature taking a case of an automobile light manufacturing industry.

The purpose of this paper is to uncover the significance of lean manufacturing technique in manufacturing environments.

Lean manufacturing is a management approach focused on incremental improvements in operations. Different lean strategies are being utilized by manufacturing industry to improve the performance of current manufacturing system processes. This study attempts to evaluate the performance of different lean manufacturing tools in the manufacturing industry of northern India. The importance level of different lean tools, important benefits achieved after successful implementation of lean manufacturing approach and benefits occurred after implementation of different lean tools have been identified. A questionnaire survey in the case company has been performed and the most important element of lean manufacturing has been implemented.

Results explicitly depict that just-in-time manufacturing is the most important element of lean manufacturing. Results indicate the net savings of rupees 242,208 annually after implementing lean manufacturing technique in a case company.

The paper demonstrates the practical application of lean technique showing how it can bring real breakthroughs in saving cost in the manufacturing industry.

One of most important tools for lean production is value stream mapping (VSM), which identifies and reduces errors, losses, waiting time and improves value adding time, leading to enhanced product quality through empowering production unit in terms of production risk and cost reduction in the long term. This paper aims to present a general concept for production flow, such that value stream can be fully understood. For this purpose, this research investigates the effect of value stream on operational losses and analyzes the process that has been conducted in preview step operationally, using the discovered pattern.

In this research, related processes were evaluated after the review of the relevant literature and after extracting operational basics of lean approach using a questionnaire, such that all factors affecting operational losses and VSM were assessed. Then comparison between the result of current state map and the result of future state map were done and analyzed. Cronbach’s alpha was calculated to test the designed questionnaire’s reliability, which resulted in an acceptable level of 0.845. The structural equation modeling method through SPSS and Smart–Partial Least Square was applied to analyze the data and test the hypotheses.

The results reveal that implementing required changes and corrections will lead directly to production process improvement, which, in turn, results in higher customer satisfaction because of cost reduction and quality enhancement. Also, tests of the hypotheses confirm that VSM affects six operational losses, namely, equipment failures, set-up and changeovers, idling and minor stoppages, reduced speed operation, scrap and rework and startup losses.

Though this study was done in a single manufacturing company, the implementation of this study delivers important results that can be deployed in other such manufacturing companies.

This tool helps to identify loss points, make right decisions, and choose the best methods and lean tools for improvement. The surveyed company can integrate lean principles and tools and achieve better results using this tool. Also, this tool could be used to analyze the process and to define necessary changes before changing the process components.

This study contributes to the body of knowledge in manufacturing research as the study regarding the effects of improvement opportunities identified through VSM on operational losses is still something new.

The overarching objective of this research is to integrate the Lean Six Sigma (LSS) framework with computer simulation to improve the production efficiency of a light-emitting diode (LED) manufacturing factory.

Recently, the idea of taking advantage of the benefits of Six Sigma and simulation models together has led both industry and the academy towards further investigation and implementation of these methodologies. From this perspective, the present research will illustrate the effectiveness of using LSS methodology in a real factory environment by using the combination of three simulation methods which are system dynamics (SD), discrete-event simulation (DES) and agent-based (AB) modelling.

The hybrid simulation method applied in this research was found to accurately mimic and model the existing real factory environment. The define, measure, analyse, control and improve (DMAIC)-based improvements showed that the applied method is able to improve machine utilization rates while balancing the workload. Moreover, queue lengths for several stations were shortened, and the average processing time was decreased by around 50%. Also, a weekly production increase of 25% was achieved while lowering the cost per unit by around 8%.

While the case study used was for a LED manufacturing system, the proposed framework could be implemented for any other existing production system. The research also meticulously presents the steps carried out for the development of the multi-method simulation model to allow readers to replicate the model and tailor it for their own case studies and projects. The hybrid model enables managers to navigate the trade-off decisions they often face when choosing advanced production output ahead of continuous improvement practices. The adoption of methodologies outlined in this paper would attain improvements in terms of queue lengths, utilization, reduced costs and improved quality and efficiency of a real, small factory. The findings suggest improvements and create awareness among practitioners for the utilization of quality tools that will provide direct benefits to their companies. Although the multi-method simulation is effective, a limitation of the current study is the lack of micro details within each station. Furthermore, the results are all based on one specific case study which is not enough to suggest and generalized findings.

This research combines the use of the three main hybrid simulation paradigms (SD, DES and AB) in a unified framework DMAIC methodology. Choosing the right models in DMAIC is important, challenging and urgently necessary. Also, this paper shows empirical evidence on its effectiveness.