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Scope of Value Stream Mapping to Initiate Lean Manufacturing: An Analysis in the Apparel Industry of Bangladesh

Scope of Value Stream Mapping to Initiate Lean Manufacturing: An Analysis in the Apparel Industry of Bangladesh

Once the target product family was chosen, the next activity will be value stream mapping (VSM) of the factory’s current state. Current state follow a product’s production (materials) path from beginning to end, then draw a visual representation of every process in the material & information flows including materials retention which will demonstrate the throughput time of first bundle from door to door. The VSM tool allows a visual representation of value streams to help identify and categorize the wastes in the current state. This map is used to plan actions to eliminate the wastes and obtain the future state.
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VALUE STREAM MAPPING AND ITS SIGNIFICANCE IN THE PRODUCTION PROCESS

VALUE STREAM MAPPING AND ITS SIGNIFICANCE IN THE PRODUCTION PROCESS

The border between process innovation and improvement of processes has been clearly established. Innovation creates in the process higher radical change leap. Improvement can be understood as continuous daily activities of people involved in a process that aims to increase the efficiency of the process itself (reducing wastes, costs, downtime, increasing performance and quality). Elementary differences between innovation and improvement of processes can be found in Table 1. When improving the entire process chain as a comprehensive system of processes it is Value Stream Mapping.
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Applying value stream mapping to eliminate waste: a case study of an original equipment manufacturer for the automotive industry

Applying value stream mapping to eliminate waste: a case study of an original equipment manufacturer for the automotive industry

Since its beginning, lean manufacturing has built a worldwide reputation based on results related to production improvement and cost reduction in several companies. This management philosophy focuses on customer value creation through the elimination of production wastes. Lean methods and techniques have spread their scope from the automotive industry to a wide range of industries and services. This article presents a case study that describes the use of the lean tool value stream mapping in the production process of automotive parts for a major automotive company. At the beginning of the project, relevant data from the process were collected and analysed. Subsequently, the initial process was mapped, the related wastes were identified, and then future processes were mapped and financial results were estimated. The proposals were presented on kaizen meetings, the action plan was discussed and the decision regarding which option to choose was taken. Consequently, the Cycle Time and the level of the workforce were reduced, the process was improved and savings were obtained.
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Aplicação do mapeamento da cadeia de valor: um estudo de caso em uma lavanderia hospitalar / Application of value stream mapping: a case study in a hospital laundry

Aplicação do mapeamento da cadeia de valor: um estudo de caso em uma lavanderia hospitalar / Application of value stream mapping: a case study in a hospital laundry

O principal objetivo do presente artigo é a aplicação da ferramenta gerencial de engenharia value stream mapping (vsm) e a elaboração de um mapa de future state em uma lavanderia hospitalar, buscando uma melhor utilização dos recursos existentes e uma redução na complexidade do fluxo processual, visto que este setor pode ser comparado a um setor industrial por apresentar entradas e saídas específicas e ciclos processuais padronizados. A metodologia utilizada para o desenvolvimento do presente trabalho foi de natureza aplicada, os objetivos foram definidos como descritivos e a abordagem foi qualitativa, por meio do método de estudo de caso, sendo o cenário estudado no presente artigo o setor de lavanderia de um hospital regional do sul de minas gerais. O cenário atual do setor foi mapeado por meio do vsm e esperou-se que a aplicação do mapeamento da cadeia de valor (vsm) trouxesse benefícios analíticos sobre questões processuais, e que o uso dessa técnica ajudasse a identificar desperdícios, perdas processuais e a levantar sugestões de melhorias, as quais possibilitam uma tomada de decisão muito mais efetiva e direcionada às metas buscadas. Os objetivos da aplicação do vsm foram alcançados no presente estudo.
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Proposal the application of DMAIC tools and value stream mapping under the perspective of the lean philosophy for process improvement : a case study

Proposal the application of DMAIC tools and value stream mapping under the perspective of the lean philosophy for process improvement : a case study

After a recent merger, the in vitro diagnostic equipment trade company in Brazil, study object, faces difficulties for its logistics flow. The work proposes the application of the DMAIC tools, contained in the context of the six sigma, and Value Stream Mapping (VSM) under the lean philosophy perspective in order to identify the focus of waste that can be improved, corroborating with lean thinking. Unlike the common application of VSM, used in manufacturing processes, this study has its application in a service chain. From the Methodology point of view, the case study uses a qualitative approach, having as strategy the bibliographics with a descriptive and explanatory objective. Additionally, it is delineated based on the DMAIC cycle to establish the industrial overview and method of conducting the process study, and conse- quently, the influence on the management by the guidelines and their impact on the management of the work routine. Thus, the VSM application is presented to control the flow of distributed inventory parts with the current and future pro- cess state maps. Finally, the analyzes show the results obtained with the reduction of the waste, from the centralization of the company’s inventory.
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View of Value stream mapping as lean healthcare's tool to see wastes and improvement points

View of Value stream mapping as lean healthcare's tool to see wastes and improvement points

According to Narayanamurthy and Gurumurthy (2014), it is already evident that the application of lean manufacturing concepts has won several business segments, including health care segments. This sector envisions a new philosophy, once industry specific, now being applied quietly in health, and successfully in several practical cases in the international literature. And it is in this context that the importance of value stream mapping in its future state, planning and designing with a focus on waste elimination, is notorious even if some goals may seem utopian at first sight, they must be pursued in a motivating and I strongly.
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Aplicação do Multi-Layer Stream Mapping para a Gestão da Eficiência de Recursos e Produtividade de um Sistema de Produção

Aplicação do Multi-Layer Stream Mapping para a Gestão da Eficiência de Recursos e Produtividade de um Sistema de Produção

É possível que, à primeira vista, o MSM possa ser indentificado como uma extensão do Value Stream Mapping, uma vez que um dos principais objetivos desta ferramenta é discretizar, ao longo dos diversos KPI’s considerados assim como dos diversos postos de trabalho, as quantidade que acrescentam, ou não, valor ao produto final. Porém, o facto de se pretender obter um valor global agregado para a eficiência do sistema em análise, e a forma sistemática original de obter esse valor, fazem com que a metodologia MSM se posicione com uma abordagem inovadora capaz de ser utilizada como ferramenta analitica ou vir a ser implementada em software de gestão de operações.
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Modified value stream mapping of airport check-in procedures

Modified value stream mapping of airport check-in procedures

Brazil’s burgeoning middle class is taking to the air in ever-increasing numbers which is stressing long-standing airport weaknesses and exposing new ones. The modernization and privatization of Brazilian airports presents opportunities to address these infrastructure and process shortcomings. While facility improvements are relatively straight forward to diagnose and develop a fix for, process improvements can be trickier to identify and address because they often involve more variables and are influenced by whose perspective is emphasized—the passenger’s or the service provider’s. When subjective criteria is added to the mix, the task becomes more difficult, necessitating the use of a valid and repeatable methodology, which is what was attempted with this study. Pairing value stream mapping with a construct for assigning magnitudes of value and waste enables decision makers to prioritize activities, even those that are subjective in nature. The application in this study of Martins et al.’s construct in a much more dynamic environment (multiple players and multiple options versus the one restaurant process [and the data obtained from only one person]) gives validity to this method of subjective examination.
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Implementação e optimização de Value Stream Mapping no sector automóvel

Implementação e optimização de Value Stream Mapping no sector automóvel

resumo O presente projecto tem como objectivo fornecer uma ferramenta de gestão completa, de forma a capacitar as pessoas que a utilizem a terem uma fonte de informação valiosa. O Value Stream Mapping é uma ferramenta de gestão de fluxos: de informação, materiais e de processos/pessoas, cujo objectivo é o de tornar evidente os fluxos/processos que gerem valor e os que não gerem valor. Assim, e tendo em conta o facto de a C.A.C.I.A. necessitar de uma ferramenta que melhore o seu desempenho, foi proposto a implementação e aplicação desta ferramenta para a fabricação dos principais componentes das caixas de velocidade de 5 velocidades (JR): Árvore Primária, Árvore Secundaria, Pinhão Louco de 1ª/2ª/3ª/4ª/5ª, Pinhão Fixo 5ª e Coroa. Uma vez que esta ferramenta é “nova” nesta organização decidiu-se começar por aplicá-la nos seus principais e mais importantes processos de fabrico, podendo, mais tarde, estender este trabalho a outros sectores.
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Multi-layer stream mapping para a gestão da eficiência de sistema marinho fechado

Multi-layer stream mapping para a gestão da eficiência de sistema marinho fechado

A aplicação do Multi-Layer Stream Mapping na gestão de eficiência de um sistema marinho fechado surge como uma oportunidade para alavancar esta ferramenta, criada na Unidade de Desenv[r]

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Value Stream Mapping metodologia Lean aplicada a uma linha de montagem

Value Stream Mapping metodologia Lean aplicada a uma linha de montagem

O Value Stream Mapping é um excelente ponto de partida para a implementação das ferramentas Lean. Através do VSM é possível ver todo o processo e identificar quais as oportunidades de melhoria possíveis de se aplicar. Todo este projeto se baseia nesta metodologia, analisando em primeiro lugar o processo de produção dos exaustores como um todo e em seguida com uma família de produtos específicos. Em ambos os casos os resultados foram extremamente positivos, no primeiro a redução em dez colaboradores, mantendo a mesma cadência de produção de exaustores, com um ganho aproximado de cento e dez mil euros anuais, uma redução significativa de stock e uma otimização das linhas de montagem e o seu supermercado. No segundo caso é de realçar uma redução em mais de cinquenta por cento do
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Implementação de uma linha modelo e value stream mapping na Ria Blades

Implementação de uma linha modelo e value stream mapping na Ria Blades

O foco principal destas ferramentas é a eliminação de desperdícios, redução de recursos desnecessários e de tempos de produção, isto é, sucintamente, fazer mais com menos. Com esta implementação, as necessidades dos consumidores são correspondidas, visto que, o produto tem maior qualidade e os custos e os tempos de ciclo do processo produtivo são reduzidos. Assim, é expectável que a implementação destas metodologias será benéfica para a obtenção do objetivo fulcral deste projeto, a diminuição do tempo de ciclo da produção de uma pá eólica de 68,5 metros. Deste modo, foram aplicadas duas ferramentas Lean neste caso de estudo, o Value Stream Mapping e a Linha Modelo. A utilização e elaboração do VSM facilitou a compreensão do fluxo do processo produtivo, dado que este é muito extenso e complexo. Por outro lado, este auxiliou também no estudo e análise de tempos de ciclo dos diversos processos e na identificação de possíveis fontes de desperdício a eliminar.
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Aplicação do Value Stream Mapping para o estudo e melhorias do processo produtivo

Aplicação do Value Stream Mapping para o estudo e melhorias do processo produtivo

Nesta dissertação é conduzido um projecto onde é aplicada a ferramenta Value Stream Mapping (VSM) para estudar e melhorar o processo produtivo de uma unidade da empresa Toyota Salvador Caetano Portugal. O VSM tem como objectivo analisar o estado actual da cadeia de valor, fluxo de materiais e de informação, e depois projectar o estado futuro e traçar o caminho até alcançar esse estado. O VSM é também frequentemente usado como rampa de lançamento para implementação da filosofia Lean numa empresa. Estando a empresa intimamente ligada à Toyota, seria de esperar algumas evidências disso mesmo no fluxo produtivo. O conhecimento do termo takt time, a existência de um sistema kanban, mesmo que muito rudimentar na linha de chassis, muitos quadros informativos fazendo alusões a Kaizen’s, algumas noções de 5S’s, heyjunka, todos estes conceitos, numa primeira vista, dão a entender que a filosofia Toyota Production
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Value Stream Mapping da cadeia logística

Value Stream Mapping da cadeia logística

Como os valores de stocks representados se referem ao final do dia, foram incluídos os valores de stock referentes a Domingo, para assim ser possível visualizar a evolução[r]

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Aplicação do Value Stream Mapping na melhoria de processo produtivo: caso de estudo na indústria automóvel

Aplicação do Value Stream Mapping na melhoria de processo produtivo: caso de estudo na indústria automóvel

Os objetivos do plano de melhoria foram alcançados e contribuíram para o planeamento estra- tégico da administração: foco em processos em série com elevado potencial de melhoria (redução[r]

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Revectorization-based shadow mapping

Revectorization-based shadow mapping

and MSM techniques suffer from light leaking for the shadow cast by the wall onto the floor (Figures 6-(b, c, e)). Light leaking is greatly reduced in EVSM (Figure 6-(d)). However, for small kernel sizes, all these four filtering techniques do not remove the shadow mapping aliasing. PCF does not suffer from light leaking, but it does not remove the jagged appearance of the shadow edges for small kernel sizes (Figure 6-(f)). RSMSS is not prone to light leak- ing artifacts and effectively reduces the perspective aliasing. How- ever, the filtering is performed in a limited extension (Figure 6-(g)). The RPCF + SMSR technique incorporates blurring into the revec- torized shadows, but the method is still prone to banding artifacts (Figure 6-(h)). High accuracy is obtained for the RPCF + RSMSS technique, which takes advantage from the 1-D smoothing filter of the RSMSS to reduce both banding and perspective artifacts of the shadow filtering even for a low-order box filter kernel (Figure 6-(i)).
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Software library for stream-based recommender systems

Software library for stream-based recommender systems

Some companies choose to do these expensive computations offline, and periodically update their recommendation model, keeping in real-time recommendations, but this scheme does not allow to keep recommendations accurate and updated since a lot of information is transferred between updates which is not being used [ 27 ]. Current incremental approaches are not vast, neither they are diversified and the ones that exist are task-specific. So, there must be another way of creating highly scalable recommender systems capable of dealing with incoming data streams keeping in real-time and updated recommendations of items to users. An effective solution for this problem is the adoption of incremental learning approaches. Each time a new data stream comes to the system, it can be observed as a rating and the new rating will be a function of the previously calculated ratings and the newest one. This way the model does not have to be recalculated again since it was calculated before. Thus, it would be useful for a library which aided the development of incremental recommender systems for highly scalable solutions to exist, and be imported by a third party as a project dependency. This would allow the development of new algorithms, the comparison between them, and since they should be built in a generic way, this would allow their appliance in real-world applications.
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TweeProfiles4: a weighted multidimensional stream clustering algorithm

TweeProfiles4: a weighted multidimensional stream clustering algorithm

algorithm only supports the former type. The data structure was adapted with the addition of a two-dimensional array that keeps the frequency of the categorical data. This approach is similar to the process that HCluStream used to extend CluStream. MStream, proposed in [ WW10 ], also fol- lows this line of thought, being an algorithm for clustering evolving heterogeneous data streams. Despite being compared to HCluStream and CluStream, it is very similar to HDenStream. This ap- proach also comprises a normalization process on every dimension, which is run at the beginning of the clustering process. DenStream is also improved by SOStream [ IDH12 ], an algorithm devel- oped with the objective of automatically adapting the threshold on density-based clustering. This is achieved by adopting the concept of competitive learning [ Koh82 ]. Both HDDStream [ NZP + 12 ] and PreDeConStream [ HSGS12 ] improve DenStream in the context of high-dimensional data by applying the concept of projected clustering. FlockStream [ FPS09 ] proposes an algorithm based on a bio-inspired model with the objective of improving the efficiency of the algorithm by reduc- ing the number of computations performed. LeaDen-Stream [ AW13 ] is an algorithm proposed as an improvement of DenStream for reducing the time complexity of the process. It introduces the concept of mini-micro and micro cluster leaders, which are dependent on the distribution of the data points inside each microcluster. This is motivated by the fact that existing microclustering algorithms ignore the inner distribution, which leads to less accuracy since only the microcluster’s centers are sent to the offline phase.
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Extracting Knowledge from Stream Behavioural Patterns

Extracting Knowledge from Stream Behavioural Patterns

The first two parts represent the struc- tured part of our model and account for the source ID and fixed d-dimensions re- spectively. These d-dimensions allow hu- man users to select information based on time, location or even other dimensions, and can be understood as an OLAP cube helping in the process of filtering informa- tion. The remaining parts of our model extract information from the content it- self and organize it based on semantic and stream similarity. Our work on semantic similarity can be found in the following publications (?; ?). The first steps towards a stream similarity model are given in this paper.
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Online clustering of trajectory data stream

Online clustering of trajectory data stream

Efficiency Analysis of the Clustering approaches. Data stream applications im- pose a limited memory constrained, it becomes difficult to provide arbitrary-shaped clustering results using conventional algorithms as DBSCAN. It is unrealistic to provide such a precise result. In the original DBSCAN, the system has to check the density connectivity for each moving object sub-trajectory which makes the approach computational costly (showed in Figure 15(a)). To discover density based clusters from trajectory data stream, CUTiS has two steps namely the creation and maintenance step (Mstep, Algorithms 3, 4 and 5), and clustering step (Cstep, Algorithm 6). In Figure 15(b), the clustering step dominates the total cost in most of the time windows. Since to merge micro-groups into a cluster, we need to detect if they are density connected which is expensive (in the worst case, it is necessary to compare all pairwise moving objects that belong to these micro-groups). However, the micro-group structure can save computation in the maintenance processing avoid accessing all data set objects in details. Our results present more gain in efficiency than DBSCAN when micro-group radius increases (it maintains less representative trajectories, i.e. less number of micro-groups). As we mentioned before, TraClus approximated in the experiments most of the time the sub-trajectory to only one segment. In this case, the distance computation is less costly than consider each sub-trajectory with many segments as CUTiS did. This is the main reason why TraClus is much faster to do clustering. However, it only essentially outperformed CUTiS when micro-group radius=eps.
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