Las estrategias en el lugar de trabajo del Partido Comunista en Argentina desde sus orígenes hasta 1943 : Células, comités de fábricas y comisiones internas

La intención de nuestro trabajo es recuperar la experiencia impulsada por el Partido Comunista (PC) a partir de su creación y hasta la irrupción del peronismo en la organización del movimiento obrero en los sitios de producción. Durante años la creencia extendida en la historiografía asociaba la militancia en los espacios de base con el modelo sindical peronista y la instalación de las comisiones internas. Recientes investigaciones demostraron el extenso entramado organizacional de base generado por el proletariado fabril en las décadas anteriores a 1943. En dicho proceso coadyuvaron las corrientes de izquierda y en particular el PC que enarboló una política específica para su inserción en las fábricas y empresas. Los ejes que guían nuestra pesquisa son variados: las formas que adquirió esta militancia de base, el impacto de las líneas estratégicas partidarias, entre otros.

Collaborative Engineering Paradigm Applied to the Aerospace Industry

Airbus designs and industrializes aircrafts using Concurrent Engineering techniques since decades. The introduction of new PLM methods, procedures and tools, and the need to reduce time-to-market, led Airbus Military to pursue new working methods. Traditional Engineering works sequentially. Concurrent Engineering basically overlaps tasks between teams. Collaborative Engineering promotes teamwork to develop product, processes and resources from the conceptual phase to the start of the serial production. The CALIPSO-neo pilot project was launched to support the industrialization process of a medium size aerostructure. The aim is to implement the industrial Digital Mock-Up (iDMU) concept and its exploitation to create shop floor documentation. In a framework of a collaborative engineering strategy, the project is part of the efforts to deploy Digital Manufacturing as a key technology for the industrialization of aircraft assembly lines. This paper presents the context, the conceptual approach and the methodology adopted.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Integrated manufacturing, empowerment, and company performance

There is controversy over whether integrated manufacturing (IM), comprising advanced manufacturing technology, just-in-time inventory control and total quality management, empowers or deskills shop floor work. Moreover, both IM and empowerment are promoted on the assumption that they enhance competitiveness. We examine these issues in a study of 80 manufacturing companies. The extent of use of IM was positively associated with empowerment (i.e., job enrichment and employee skill enhancement), but, with the minor exception of AMT, bore little relationship with subsequent company performance. In contrast, the extent of empowerment within companies predicted the subsequent level of company performance controlling for prior performance, with the effect on productivity mediating that on profit. Copyright © 2004 John Wiley & Sons, Ltd.

The impact of NC machinery upon manufacturing industry

The changing face of industry due to the adoption of `New Technology' is briefly discussed, as are the corresponding structural changes in the workforce. The adoption of NC machinery is identified as one of the major innovations affecting the structure of industry. The development of NC machinery, and of relevant programming techniques are reviewed, and the problems arising from its initial sponsorship by the aerospace industry are highlighted. The process of its subsequent diffusion into industry is reviewed. Skill levels adopted for NC use in Britain and Germany are discussed, and analysed to create a structural pattern. These classifications of skill levels are then used to examine the organisational structures adopted by companies utilising NC machines. The greater use made of higher level shop floor skills by German companies is discussed. The results of two surveys of the use made of NC by companies in the North East of England are presented. Effective company organisation for NC use is described, and lack of foresight is shown to lead to vulnerability problems where skills can become concentrated in a few key people. This led to closure of a company in one instance. It is shown that small sub-contract companies have adopted a highly skilled shop floor workforce, and that they have survived in the present hostile economic environment, whilst companies who have used NC to de-skill the shop floor contracted dramatically in the same period. The lack of awareness of the potential for reviewing the product design in relation to the flexibility of NC, so leading to reductions in work in progress levels, is highlighted. Recommendations for skill structures appropriate to various sized companies and suitable training programs are presented to ensure that the full potential of NC machinery is achieved.

Computer integrated monitoring

Computer integrated monitoring is a very large area in engineering where on-line, real time data acquisition with the aid of sensors is the solution to many problems in the manufacturing industry as opposed to the old data logging method by graphics analysis. The raw data which is collected this way however is useless in the absence of a proper computerized management system. The transfer of data between the management and the shop floor processes has been impossible in the past unless all the computers in the system were totally compatible with each other. This limits the efficiency of the systems because they get governed by the limitations of the computers. General Motors of U.S.A. have recently started research on a new standard called the Manufacturing Automation Protocol (MAP) which is expected to allow data transfer between different types of computers. This is still in early development stages and also is currently very expensive. This research programme shows how such a shop floor data acquisition system and a complete management system on entirely different computers can be integrated together to form a single system by achieving data transfer communications using a cheaper but a superior alternative to MAP. Standard communication character sets and hardware such as ASCII and UARTs have been used in this method but the technique is so powerful that totally incompatible computers are shown to run different programs (in different languages) simultaneously and yet receive data from each other and process in their own CPUs with no human intervention.

The influence of cutting tool geometry upon aspects of chip flow and tool wear:a theoretical, three dimensional examination of the cutting geometry and the shape of the twist drill

This work is undertaken in the attempt to understand the processes at work at the cutting edge of the twist drill. Extensive drill life testing performed by the University has reinforced a survey of previously published information. This work demonstrated that there are two specific aspects of drilling which have not previously been explained comprehensively. The first concerns the interrelating of process data between differing drilling situations, There is no method currently available which allows the cutting geometry of drilling to be defined numerically so that such comparisons, where made, are purely subjective. Section one examines this problem by taking as an example a 4.5mm drill suitable for use with aluminium. This drill is examined using a prototype solid modelling program to explore how the required numerical information may be generated. The second aspect is the analysis of drill stiffness. What aspects of drill stiffness provide the very great difference in performance between short flute length, medium flute length and long flute length drills? These differences exist between drills of identical point geometry and the practical superiority of short drills has been known to shop floor drilling operatives since drilling was first introduced. This problem has been dismissed repeatedly as over complicated but section two provides a first approximation and shows that at least for smaller drills of 4. 5mm the effects are highly significant. Once the cutting action of the twist drill is defined geometrically there is a huge body of machinability data that becomes applicable to the drilling process. Work remains to interpret the very high inclination angles of the drill cutting process in terms of cutting forces and tool wear but aspects of drill design may already be looked at in new ways with the prospect of a more analytical approach rather than the present mix of experience and trial and error. Other problems are specific to the twist drill, such as the behaviour of the chips in the flute. It is now possible to predict the initial direction of chip flow leaving the drill cutting edge. For the future the parameters of further chip behaviour may also be explored within this geometric model.

Evaluating the impact of design decisions on the financial performance of manufacturing companies

Product design decisions can have a significant impact on the financial and operation performance of manufacturing companies. Therefore good analysis of the financial impact of design decisions is required if the profitability of the business is to be maximised. The product design process can be viewed as a chain of decisions which links decisions about the concept to decisions about the detail. The idea of decision chains can be extended to include the design and operation of the 'downstream' business processes which manufacture and support the product. These chains of decisions are not independent but are interrelated in a complex manner. To deal with the interdependencies requires a modelling approach which represents all the chains of decisions, to a level of detail not normally considered in the analysis of product design. The operational, control and financial elements of a manufacturing business constitute a dynamic system. These elements interact with each other and with external elements (i.e. customers and suppliers). Analysing the chain of decisions for such an environment requires the application of simulation techniques, not just to any one area of interest, but to the whole business i.e. an enterprise simulation. To investigate the capability and viability of enterprise simulation an experimental 'Whole Business Simulation' system has been developed. This system combines specialist simulation elements and standard operational applications software packages, to create a model that incorporates all the key elements of a manufacturing business, including its customers and suppliers. By means of a series of experiments, the performance of this system was compared with a range of existing analysis tools (i.e. DFX, capacity calculation, shop floor simulator, and business planner driven by a shop floor simulator).

The design of a support department simulator for use in the design of manufacturing systems

Manufacturing firms are driven by competitive pressures to continually improve the effectiveness and efficiency of their organisations. For this reason, manufacturing engineers often implement changes to existing processes, or design new production facilities, with the expectation of making further gains in manufacturing system performance. This thesis relates to how the likely outcome of this type of decision should be predicted prior to its implementation. The thesis argues that since manufacturing systems must also interact with many other parts of an organisation, the expected performance improvements can often be significantly hampered by constraints that arise elsewhere in the business. As a result, decision-makers should attempt to predict just how well a proposed design will perform when these other factors, or 'support departments', are taken into consideration. However, the thesis also demonstrates that, in practice, where quantitative analysis is used to evaluate design decisions, the analysis model invariably ignores the potential impact of support functions on a system's overall performance. A more comprehensive modelling approach is therefore required. A study of how various business functions interact establishes that to properly represent the kind of delays that give rise to support department constraints, a model should actually portray the dynamic and stochastic behaviour of entities in both the manufacturing and non-manufacturing aspects of a business. This implies that computer simulation be used to model design decisions but current simulation software does not provide a sufficient range of functionality to enable the behaviour of all of these entities to be represented in this way. The main objective of the research has therefore been the development of a new simulator that will overcome limitations of existing software and so enable decision-makers to conduct a more holistic evaluation of design decisions. It is argued that the application of object-oriented techniques offers a potentially better way of fulfilling both the functional and ease-of-use issues relating to development of the new simulator. An object-oriented analysis and design of the system, called WBS/Office, are therefore presented that extends to modelling a firm's administrative and other support activities in the context of the manufacturing system design process. A particularly novel feature of the design is the ability for decision-makers to model how a firm's specific information and document processing requirements might hamper shop-floor performance. The simulator is primarily intended for modelling make-to-order batch manufacturing systems and the thesis presents example models created using a working version of WBS/Office that demonstrate the feasibility of using the system to analyse manufacturing system designs in this way.

New measures of job control, cognitive demand and production responsibility

Recent research has highlighted several job characteristics salient to employee well-being and behavior for which there are no adequate generally applicable measures. These include timing and method control, monitoring and problem-solving demand, and production responsibility. In this article, an attempt to develop measures of these constructs provided encouraging results. Confirmatory factor analyses applied to data from 2 samples of shop-floor employees showed a consistent fit to a common 5-factor measurement model. Scales corresponding to each of the dimensions showed satisfactory internal and test–retest reliabilities. As expected, the scales also discriminated between employees in different jobs and employees working with contrasting technologies.

Professional standards research:job satisfaction and innovation

Job satisfaction is a significant predictor of organisational innovation – especially where employees (including shop-floor workers) experience variety in their jobs and work in a single-status environment. The relationship between job satisfaction and performance has long intrigued work psychologists. The idea that "happy workers are productive workers" underpins many theories of performance, leadership, reward and job design. But contrary to popular belief, the relationship between job satisfaction and performance at individual level has been shown to be relatively weak. Research investigating the link between job satisfaction and creativity (the antecedent to innovation) shows that job dissatisfaction promotes creative outcomes. The logic is that those who are dissatisfied (and have decided to stay with the organisation) are determined to change things and have little to lose in doing so (see JM George & J Zhou, 2002). We were therefore surprised to find in the course of our own research into managerial practices and employee attitudes in manufacturing organisations that job satisfaction was a highly significant predictor of product and technological innovation. These results held even though the research was conducted longitudinally, over two years, while controlling for prior innovation. In other words, job satisfaction was a stronger predictor of innovation than any pre-existing orientation organisations had towards working innovatively. Using prior innovation as a control variable, as well as a longitudinal research design, strengthened our case against the argument that people are satisfied because they belong to a highly innovative organisation. We found that the relationship between job satisfaction and innovation was stronger still where organisations showed that they were committed to promoting job variety, especially at shop-floor level. We developed precise instruments to measure innovation, taking into account the magnitude of the innovation both in terms of the number of people involved in its implementation, and how new and different it was. Using this instrument, we are able to give each organisation in our sample a "score" from one to seven for innovation in areas ranging from administration to production technology. We found that much innovation is incremental, involving relatively minor improvements, rather than major change. To achieve sustained innovation, organisations have to draw on the skills and knowledge of employees at all levels. We also measured job satisfaction at organisational level, constructing a mean "job satisfaction" score for all organisations in our sample, and drawing only on those companies whose employees tended to respond in a similar manner to the questions they were asked. We argue that where most of the workforce experience job satisfaction, employees are more likely to collaborate, to share ideas and aim for high standards because people are keen to sustain their positive feelings. Job variety and single-status arrangements further strengthen the relationship between satisfaction and performance. This makes sense; where employees experience variety, they are exposed to new and different ideas and, provided they feel positive about their jobs, are likely to be willing to try to apply these ideas to improve their jobs. Similarly, staff working in single-status environments where hierarchical barriers are reduced are likely to feel trusted and valued by management and there is evidence (see G Jones & J George, 1998) that people work collaboratively and constructively with those they trust. Our study suggests that there is a strong business case for promoting employee job satisfaction. Managers and HR practitioners need to ensure their strategies and practices support and sustain job satisfaction among their workforces to encourage constructive, collaborative and creative working. It is more important than ever for organisations to respond rapidly to demands of the external environment. This study shows the positive association between organisational-level job satisfaction and innovation. So if a happy workforce is the key to unlocking innovation and organisations want to thrive in the global economy, it is vital that managers and HR practitioners pay close attention to employee perceptions of the work environment. In a world where the most innovative survive it could make all the difference.

Total productive maintenance implementation in the newspaper printing industry:an action research approach

The objective of Total Productive Maintenance (TPM) is to maximise plant and equipment effectiveness, to create a sense of ownership for operators, and promote continuous improvement through small group activities involving production, engineering and maintenance personnel. This paper describes and analyses a case study of TPM implementation at a newspaper printing house in Singapore. However, rather than adopting more conventional implementation methods such as employing consultants or through a project using external training, a unique approach was adopted based on Action Research using a spiral of cycles of planning, acting observing and reflecting. An Action Research team of company personnel was specially formed to undertake the necessary fieldwork. The team subsequently assisted with administering the resulting action plan. The main sources of maintenance and operational data were from interviews with shop floor workers, participative observation and reviews conducted with members of the team. Content analysis using appropriate statistical techniques was used to test the significance of changes in performance between the start and completion of the TPM programme. The paper identifies the characteristics associated with the Action Research method when used to implement TPM and discusses the applicability of the approach in related industries and processes.

A novel algorithm of posture best fit based on key characteristics for large components assembly

Measurement and variation control of geometrical Key Characteristics (KCs), such as flatness and gap of joint faces, coaxiality of cabin sections, is the crucial issue in large components assembly from the aerospace industry. Aiming to control geometrical KCs and to attain the best fit of posture, an optimization algorithm based on KCs for large components assembly is proposed. This approach regards the posture best fit, which is a key activity in Measurement Aided Assembly (MAA), as a two-phase optimal problem. In the first phase, the global measurement coordinate system of digital model and shop floor is unified with minimum error based on singular value decomposition, and the current posture of components being assembly is optimally solved in terms of minimum variation of all reference points. In the second phase, the best posture of the movable component is optimally determined by minimizing multiple KCs' variation with the constraints that every KC respectively conforms to its product specification. The optimal models and the process procedures for these two-phase optimal problems based on Particle Swarm Optimization (PSO) are proposed. In each model, every posture to be calculated is modeled as a 6 dimensional particle (three movement and three rotation parameters). Finally, an example that two cabin sections of satellite mainframe structure are being assembled is selected to verify the effectiveness of the proposed approach, models and algorithms. The experiment result shows the approach is promising and will provide a foundation for further study and application. © 2013 The Authors.

Munkaszervezés a lean termelésben – mit magyaráznak a termelésmenedzsment koncepciók = Work organization in lean production – what production concepts explain

A tanulmány a lean termelés munkaszervezését három termelésmenedzsment koncepció segítségével vizsgálja. Az egyes koncepciók a szervezet eltérő metszeteit érintik: (1) a termék-folyamat mátrix (Hayes és Wheelwright, 1979) a termék és a folyamat jellemzőit helyezi középpontba. A lean hatására a szervezet a mátrixban a nagyobb választék és a folyamat alapú működés (nagyobb függőség) irányába mozdul el. Az elmozdulást üzemi szinten a magas elkötelezettségű munkavégzési rendszer gyakorlatainak bevezetése kíséri, mivel azok támogatják a rugalmas működést, a gyors kommunikációt és problémamegoldást. Az elmozdulás „minősége” és így a munkaszervezési gyakorlatok használata (mélyég, száma, munkavállalók bevonása) nagyban függ a termelési stratégiától és a lean érettségtől. (2) A termelési stratégia szakaszai (Wheelwright és Hayes, 1985) a termelés üzleti stratégiában játszott szerepét elemzik. A lean termelés összeegyeztethető a termelési stratégia harmadik szakaszának „command és control” szemléletmódjával. Az ilyen lean termelők költégfókuszúak, a hagyományos munkaerőképben gondolkodnak és körükben kevésbé jellemző az új emberi erőforrás gyakorlatok használata. A lean termelés adaptálása ösztönözheti a vállalatokat a termelési stratégia negyedik szintje felé. A negyedik szint a bevonásra, problémamegoldásra és tanulásra épít, amely megfelel a lean „emberek tisztelete” pillérének. (3) A lean érettségi modell (Hines és társai, 2004) a lean szervezeten belüli elmélyülését és terjedését mutatja be. A lean utazás során a vállalatok az eszköz alapú megközelítéstől a komplex értékrendszerben gondolkodó lean szervezet felé haladnak. A technikai tudásanyag egyre szélesebb körűvé válik, ami rávilágít a tudásátadás (személyek közöttire, de akár struktúrákba, folyamatokba építése is) képességének jelentőségére. Az emberi erőforrás gyakorlatok folyamatosan jelennek meg. De csak a legfejlettebb szakasz, a lean tanuló szervezet megjelenése teszi valóban szükségessé a munkavállalói kép újragondolását is. = This paper examines work organization in lean production with the help of three production concepts. These concepts embrace different dimensions of the organization: (1) the product-process matrix (Hayes and Wheelwright, 1979) is about product and process characteristics. Due to the lean the organization shifts within the matrix – towards higher variability and flow (higher level of interdependencies). On the shop floor the shift is accompanied by the introduction of high commitment work system’s practices, since those support flexible operations, fast communication and problem-solving. The „quality” of the shift and hence the application of these work practices (number of practices, their embeddeness, employee involvement) highly depends on manufacturing strategy and lean maturity. (2) The concept of stages of manufacturing strategy (Wheelwright and Hayes, 1985) analyzes the role of the manufacturing function in the business strategy. Lean production is compatible with the „command and control” approach of the third stage of manufacturing strategy. These lean producers are cost-driven, they have the traditional approach of employees and apply new work organization practices to a less extent. However, the implementation of lean production may drive these companies to the fourth stage. The fourth stage of manufacturing strategy is based on employee involvement, problem-solving and learning. This stage is in full accordance with the „respect for people” pillar of lean production. (3) Lean maturity (Hines et al., 2004) shows the path how lean management deepens and expands within an organization. During the lean journey, companies progress from the tool-based approach to the complex lean value system. The technical knowledge of lean becomes more and more comprehensive and it points out the crucial importance of knowledge conversion capabilities (intrapersonal or even how to build knowledge into structures, processes). Work organization practices constantly appear with the progress, but the review of the traditional approach of employees is only essential at the most advanced stage, when an organization becomes lean learning organization.