Using Lean-Sigma for the Integration of Two Products During a Ramp-Up Event

2020 ◽  
pp. 954-976
Author(s):  
Noe Alba-Baena ◽  
Francisco J. Estrada ◽  
Oswaldo Omar Sierra Torres
Keyword(s):  
Statistical Analysis ◽  
Production Process ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Production Line ◽  
Lean Manufacturing ◽  
New Product ◽  
Quality Level ◽  
Manufacturing Environment ◽  
Improvement Methodologies

Keeping up the quality level in in a manufacturing environment has become an issue when trying to start the production of a new product which is in a ramp-up stage into a running production line ramp-down model. If production of the old model is ended too fast will make shortages in the customer supply, and will have excessive inventory numbers of the newer product. Trying the re-design in a production line to keep building the old model while incorporating the newer tends to create an undesirable impact on quality and productivity. Nowadays, continuous improvement methodologies like Lean and Six Sigma are used to solve this challenge. While Lean Manufacturing tends to be efficient for quick fixes, Six Sigma works better when there is plenty of time to conduct deeper statistical analysis. This chapter describes a combination of Lean Manufacturing speed with the Six Sigma analysis' power. Combined to maintain the quality and productivity of a production process during such conditions.

Using Lean-Sigma for the Integration of Two Products during a Ramp-Up Event

2016 ◽  
pp. 405-427 ◽  
Author(s):  
Noe Alba-Baena ◽  
Francisco J. Estrada ◽  
Oswaldo Omar Sierra Torres
Keyword(s):  
Statistical Analysis ◽  
Production Process ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Production Line ◽  
Lean Manufacturing ◽  
New Product ◽  
Quality Level ◽  
Manufacturing Environment ◽  
Improvement Methodologies

Keeping up the quality level in in a manufacturing environment has become an issue when trying to start the production of a new product which is in a ramp-up stage into a running production line ramp-down model. If production of the old model is ended too fast will make shortages in the customer supply, and will have excessive inventory numbers of the newer product. Trying the re-design in a production line to keep building the old model while incorporating the newer tends to create an undesirable impact on quality and productivity. Nowadays, continuous improvement methodologies like Lean and Six Sigma are used to solve this challenge. While Lean Manufacturing tends to be efficient for quick fixes, Six Sigma works better when there is plenty of time to conduct deeper statistical analysis. This chapter describes a combination of Lean Manufacturing speed with the Six Sigma analysis' power. Combined to maintain the quality and productivity of a production process during such conditions.

Why Are There So Many Different Continuous Improvement Models?

2019 ◽  
Vol 9 (1) ◽  
pp. 73-91 ◽  
Author(s):  
Brian J. Galli
Keyword(s):  
Quality Management ◽  
Total Quality Management ◽  
Continuous Improvement ◽  
Business Process ◽  
Six Sigma ◽  
Lean Manufacturing ◽  
Profit Maximization ◽  
Customer Retention ◽  
Total Quality ◽  
Maximum Profit

This article examines the implementation of continuous improvement patterns and the various continuous improvement (CI) models used in an organization. Despite the size of an organization, the goal is to achieve the maximum profit by pursuing continuous improvement. There are certain models and theories used in organizations for this reason, which include total quality management, business process re-engineering, Six Sigma, and Lean manufacturing methodology. These models are not only concerned with customer retention and profit maximization, but they are also equally effective for the employee's wellbeing. Different methodologies used in continuous improvement processes will help industrial engineers simplify complex tasks by applying CI tools to different situations. However, the key is to understand what tools and models are appropriate for each application.

scholarly journals Pendekatan Lean Manufacturing dalam Proses Produksi Kerajinan Bordir Sulaman dengan Metode Manajemen Berbasis Aktivitas

2019 ◽  
Vol 2 (4) ◽  
Author(s):  
Anizar ◽  
A. Rahim Matondang ◽  
Hamida Hasan ◽  
Delilah Mentari
Keyword(s):  
Production Process ◽  
Continuous Improvement ◽  
Cost Efficiency ◽  
Lean Manufacturing ◽  
Business Management ◽  
Production Costs ◽  
Production Waste ◽  
Total Production ◽  
Production Output ◽  
Domestic Products

Sulam bayangan merupakan produk sektor kreatif yang berkontribusi bagi produk domestik bruto namun menuntut efisiensi dan efektivitas untuk memenangkan persaingan antar pelaku usaha. Efisiensi akan mengurangi waste aktivitas produksi dan mengurangi biaya produksi yang dibutuhkan. Pada proses produksi kerajinan sulam bayangan masih terdapat waste berupa aktivitas yang tidak bernilai tambah yang berpengaruh terhadap output produksi. Permasalahan tersebut dapat diselesaikan dengan pendekatan lean manufacturing untuk menciptakan continuous improvement pada proses produksi dengan metode Activity Based Management (ABM). Penerapan ABM menciptakan efisiensi biaya yang menekankan pengelolaan bisnis berdasarkan aktivitas. Perbaikan yang dilakukan yaitu eliminasi dan penggabungan elemen kerja pemeriksaan motif dan sulaman. Hasilnya adalah efisiensi biaya produksi sebesar 4,89% dan waktu produksi sebesar 6,07%.   Shadow embroidery is a creative sector product that contributes to gross domestic products but requires funds and assistance to win competition among companies. Efficiency will reduce production waste and reduce the required production costs. In the process of producing shadow embroidery craft it is still a waste containing activities that are not added added to the production output. These problems can be discussed with lean manufacturing to create continuous improvement in the production process with the Activity Based Management (ABM) method. Implementation of AB Creating cost efficiency that governs business management based on activity. The improvements made are elimination and incorporation of work elements to examine motifs and embroidery. Total production costs amounted to 4.89% and production costs amounted to 6.07%.

Activity-Based Costing and Cost Interdependencies among Products: The Denim Finishing Company

2005 ◽  
Vol 20 (1) ◽  
pp. 51-62 ◽  
Author(s):  
Dennis Caplan ◽  
Nahum D. Melumad ◽  
Amir Ziv
Keyword(s):  
Production Process ◽  
Production Line ◽  
New Product ◽  
Cost Accounting ◽  
Activity Based Costing ◽  
Cost Information ◽  
Accounting Systems ◽  
Full Cost ◽  
Level Information ◽  
The Cost

A fictional example illustrates how interdependencies among products in the production process, and the costs associated with those interdependencies, challenge the ability of cost accounting systems to generate decision-useful product cost information. The cost interdependency in the current example is a production-line change-over cost that is incurred to retool a machine whenever the production process changes from one product to another. Both marginal costing and full cost activity-based costing (ABC) are employed in an attempt to provide decision-relevant product-level information in connection with the decision to add a new product.

scholarly journals Peningkatan Kualitas Produk dan Minimasi Pemborosan Dengan Mengunakan Pendekatan Six Sigma Pada Perusahaan Pakan Ternak

2020 ◽  
Vol 17 (2) ◽  
pp. 73
Author(s):  
Katon Muhammad ◽  
Kukuh Winarso ◽  
Ida Lumintu
Keyword(s):  
Production Process ◽  
Air Temperature ◽  
Design Of Experiment ◽  
Six Sigma ◽  
Production Line ◽  
Animal Feed ◽  
Raw Materials ◽  
Existing Problems ◽  
And Control

PT. XYZ is one of the animal feed companies which has some of the largest production units in Indonesia. This Feed Company has several brands of products on the market. The company's production line is indicated to have a problem, namely product defects. Defective products caused by the production process and also the process of storing raw materials and finished materials in the company. Related to the six sigma in it has a phase of define, measure, analyze, improve and control phases, is chosen to overcome the existing problems. From the define, measure and analyze phase, it is known that there are significant defects, namely defects with flea attributes in the production process, textures, lumps, and ticks in the inventory. From the results of the RPN assessment, it is known that tick defects on the production line are valued at 168, text 105 and ticks in the production process 90 so that from the results of the assessment the RPN is given recommendations for improvement with consideration of the highest RPN value. The recommended improvement recommendations are the installation of blowers and air temperature regulators in the company's storage section, conduct a design of experiment in stages to select the best raw materials by considering the quality problems of the products produced and thirdly, the improvement of the cleaning schedule in the cooler, spoting and also rotex on production machines to minimize the cause of defects.

MDAIC – a Six Sigma implementation strategy in big data environments

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siim Koppel ◽  
Shing Chang
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Product Quality ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Production System ◽  
Competitive Advantages ◽  
Manufacturing Environment ◽  
Content Type ◽  
And Control

Purpose Modern production facilities produce large amounts of data. The computational framework often referred to as big data analytics has greatly improved the capabilities of analyses of large data sets. Many manufacturing companies can now seize this opportunity to leverage their data to gain competitive advantages for continuous improvement. Six Sigma has been among the most popular approaches for continuous improvement. The data-driven nature of Six Sigma applied in a big data environment can provide competitive advantages. In the traditional Six Sigma implementation – define, measure, analyze, improve and control (DMAIC) problem-solving strategy where a human team defines a project ahead of data collection. This paper aims to propose a new Six Sigma approach that uses massive data generated to identify opportunities for continuous improvement projects in a manufacturing environment in addition to human input in a measure, define, analyze, improve and control (MDAIC) format. Design/methodology/approach The proposed Six Sigma strategy called MDAIC starts with data collection and process monitoring in a manufacturing environment using system-wide monitoring that standardizes continuous, attribute and profile data into comparable metrics in terms of “traffic lights.” The classifications into green, yellow and red lights are based on pre-control charts depending on how far a measurement is from its target. The proposed method monitors both process parameters and product quality data throughout a hierarchical production system over time. An attribute control chart is used to monitor system performances. As the proposed method is capable of identifying changed variables with both spatial and temporal spaces, Six Sigma teams can easily pinpoint the areas in need to initiate Six Sigma projects. Findings Based on a simulation study, the proposed method is capable of identifying variables that exhibit the biggest deviations from the target in the Measure step of a Six Sigma project. This provides suggestions of the candidates for the improvement section of the proposed MDAIC methodology. Originality/value This paper proposes a new approach for the identifications of projects for continuous improvement in a manufacturing environment. The proposed framework aims to monitor the entire production system that integrates all types of production variables and the product quality characteristics.

scholarly journals Implementation of Lean Six Sigma for production process optimization in a paper production company

2021 ◽  
Vol 14 (3) ◽  
pp. 661
Author(s):  
Adefemi Adeodu ◽  
Mukondeleli Grace Kanakana-Katumba ◽  
Maladzhi Rendani
Keyword(s):  
Production Process ◽  
Real Time ◽  
Six Sigma ◽  
Production Line ◽  
Lean Six Sigma ◽  
Production Performance ◽  
Paper Production ◽  
Time Problem ◽  
Production Company ◽  
Cycle Efficiency

Purpose: This study aimed at implementing lean six sigma to evaluate the productivity and manufacturing waste in the production line of a paper companyMethodology/Approach: The study is a case study in nature. The method illustrates how lean six sigma (LSS) is used to evaluate the existing production process in a paper production company with focus on productivity and manufacturing waste. The study considered a real-time problem of customer’s dissatisfaction. The gathered data is based on machine functionality (up time, down time and cycle time); materials and labour flow at every process stages of the production line. The optimization of the production process was based on lean tools like value stream mapping, process cycle efficiency, Kaizen, 5S and pareto chartFindings: Based on lean six sigma application, it was discovered that the present production performance was below standard and more manufacturing wastes were generated. The present productivity and manufacturing wastes are reported as low process cycle efficiency (23.4 %), low takt time (4.11 sec), high lead time (43200sec), high number of products not conforming to six sigma values, high down time (32.64 %) and excess labour flow (33). After the implementation of the lean six sigma tools for certain period of time, there are lots of improvements in the production line in terms of all the parameters considered.Research Limitation/ Implications:  The study has demonstrated an application of lean six sigma in the case of solving real-time problems of productivity and manufacturing wastes which have a direct implication on customer’s satisfaction. The lesson learned and implications presented can still be further modeled using some lean based software for validityOriginality/Value: The study has contributed to the body of knowledge in the field of LSS with focus to process based manufacturing, unlike most literature in the field concentrate more on discrete based manufacturing.   

scholarly journals Barriers and Enablers for Continuous Improvement Methodologies within the Irish Pharmaceutical Industry

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 73
Author(s):  
Olivia McDermott ◽  
Jiju Antony ◽  
Michael Sony ◽  
Stephen Daly
Keyword(s):  
Pharmaceutical Industry ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Internal Audit ◽  
Global Scale ◽  
Lean Six Sigma ◽  
Improvement Methodologies ◽  
Regulatory Culture ◽  
Relevant Finding ◽  
Compliance Versus

This study aims to investigate the barriers that exist when implementing continuous improvement methodologies, such as Lean Six Sigma (LSS), within the Irish Pharma industry. The main finding of this study is that 45% of participants perceived that a highly regulated environment could be a barrier to continuous improvement implementation, while 97% of respondents utilised Continuous improvement (CI) methods, such as Lean, Six Sigma, and LSS, within their organisations. While the International Conference of Harmonisation integrates CI into its Pharmaceutical Quality Systems (PQS) regulations, the highest motivation for CI implementation amongst the Irish Pharma industry is to improve Productivity and Quality. The main obstacles highlighted for CI implementation in Pharma attributed to stringent regulatory regimes were fear of extra validation activity, a compliance versus quality culture, and a regulatory culture of being “safe”. Another relevant finding presented in this paper is that participants CI LSS tools are very strongly integrated into the pharma industries corrective and preventative action system, deviations, and internal audit systems. Limitations of the research are that all the data collected in the survey came from professionals working for multinational Pharmaceutical companies based in Ireland. The authors understand that this is the first research focused on the barriers and status of CI initiatives in the pharmaceutical industry. The results of this study represent an important step towards understanding the enablers and obstacles for the use of continuous improvement methodologies in pharmaceutical manufacturing industries on a global scale.

scholarly journals Do Private Equity Owned Firms Have Better Management Practices?

2015 ◽  
Vol 105 (5) ◽  
pp. 442-446 ◽  
Author(s):  
Nicholas Bloom ◽  
Raffaella Sadun ◽  
John Van Reenen
Keyword(s):  
Continuous Improvement ◽  
Lean Manufacturing ◽  
Private Equity ◽  
Management Practices ◽  
New Product ◽  
New Product Introduction ◽  
Product Introduction ◽  
Listed Firms ◽  
Privately Owned ◽  
Survey Measure

Using an innovative survey measure of management practices on over 15,000 firms, we find private equity firms are better managed than government, family, and privately owned firms, and have similar management to publicly listed firms. This is true both in developed and developing countries. Looking at management practices in detail we find that private equity owned firms have strong people management practices (hiring, firing, pay, and promotions), but even stronger monitoring management practices (lean manufacturing, continuous improvement, and monitoring). Plant managers working in private equity owned firms also report greater autonomy from headquarters over sales, marketing, and new product introduction.

Perencanaan Pengendalian Kualitas Produk Pakaian Bayi dengan Metode Six Sigma Pada CV. AGP

JEMAP ◽  
2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Albertus Reynaldo Kurniawan ◽  
Bayu Prestianto
Keyword(s):  
Quality Control ◽  
Continuous Improvement ◽  
Six Sigma ◽  
Screen Printing ◽  
Control Method ◽  
Operational Performance ◽  
Machine Maintenance ◽  
Quality Product ◽  
Break Time ◽  
And Control

Quality control becomes an important key for companies in suppressing the number of defective produced products. Six Sigma is a quality control method that aims to minimize defective products to the lowest point or achieve operational performance with a sigma value of 6 with only yielding 3.4 defective products of 1 million product. Stages of Six Sigma method starts from the DMAIC (Define, Measure, Analyze, Improve and Control) stages that help the company in improving quality and continuous improvement. Based on the results of research on baby clothes products, data in March 2018 the percentage of defective products produced reached 1.4% exceeding 1% tolerance limit, with a Sigma value of 4.14 meaning a possible defect product of 4033.39 opportunities per million products. In the pareto diagram there were 5 types of CTQ (Critical to Quality) such as oblique obras, blobor screen printing, there is a fabric / head cloth code on the final product, hollow fabric / thin fabric fiber, and dirty cloth. The factors caused quality problems such as Manpower, Materials, Environtment, and Machine. Suggestion for consideration of company improvement was continuous improvement on every existing quality problem like in Manpower factor namely improving comprehension, awareness of employees in producing quality product and improve employee's accuracy, Strength Quality Control and give break time. Materials by making the method of cutting the fabric head, the Machine by scheduling machine maintenance and the provision of needle containers at each employees desk sewing and better environtment by installing exhaust fan and renovating the production room.

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