The aim of this article is to identify opportunities for using synergies obtained by incorporation of the two methods of management: Lean Management and Agile Management on the example of the process of column concreting. Despite the seemingly contradictory assumptions the two concepts complement each other in analysed example. The strategy is based on using the idea of "one piece flow" in accordance with the Lean Management which led to a reduction of costs due to increased turnover of formwork. At the same time the success of the project resulted in a significant dependence on the ability to provide a rapid response to changing conditions during in the maturation of concrete (depending on weather conditions, which can be expected on the basis of projections having different reliability). The simultaneous use of Lean and Agile Management allowed to achieve positive results for different scenarios of environment impact on the analysed process.

Industry 4.0 promises to make manufacturing processes more efficient using modern technologies like cyber-physical systems, internet of things, cloud computing and big data analytics. Lean Management (LM) is one of the most widely applied business strategies in recent decades. Thus, implementing Industry 4.0 mostly means integrating technologies in companies that already operate according to LM. However, due to the novelty of the topic, research on how LM and Industry 4.0 can be integrated is still under development. This paper explores the synergic relationship between these two domains by identifying six examples of real cases that address LM-Industry 4.0 integration in the extant literature. The goal is to make explicit the best practices that are being implemented by six distinct industrial sectors

The situation on the construction market is difficult. One way to improve it can be to implement modern methods and techniques related to the lean management in construction. The article presents an algorithm supporting the selection of appropriate Lean Management tools and techniques for construction companies using AHP method. The efficiency of the proposed algorithm is illustrated by a case study consisting of a small construction company performing insulation works in a multifamily house. The presented approach is part of the broader research work carried out by the authors in the field of improving construction processes and verifying the efficiency and effectiveness of Lean Management methods and techniques construction works.

The purpose of this research is to develop a Lean-RFID based waste identification system (LRWIS) for small-medium manufacturing companies. The specific objective of this research is to develop and implement the LRWIS from integrating the appropriate lean tools and advanced technologies for wastes reduction and inventory management. Subsequently, the framework was converted into a system for a small-medium sized wood processing manufacturer in Malaysia and integrated into a computerized program. The LRWIS can monitor real-time inventory and production status so the manufacturer can optimise the quantity of the primary products and deliver them on time as per the RFID information of each container. The manufacturer can also make decision instantly for controlling and changing different products in the production progress. The system provides simple constructed framework under a low cost infrastructure, yet it is of practical value in reducing the wastes and also optimising the production process.

This paper introduces the Lean School, a Learning Factory, along with a “game” of physical

simulation that is developed in it. All this is focused on teaching-learning, both of students

and professionals, of the potential advantages offered by the implementation of the Lean

Production in the organizations.

The participants gain a practical experience, based on experimental learning, which gives

them a better understanding of the principles and tools of Lean philosophy.

This physical environment is not limited to theoretical teaching, but goes beyond and implements

a production system near a real one. It starts from a configuration of a production

plant with an unbalanced system and throughout the different iterations, called productions,

introduces and implement the Lean principles, which makes its participants acquire

not only knowledge but also the skills needed to implement an efficient production in their

organizations.

All the constituent elements of the system will be described briefly: the product, the variations

thereof, the initial design with its layout, as well as the subsequent productions, and

the results of learning of each one.

Understanding of how to implement Lean successfully and how it contributes to performance in manufacturing organizational is still relatively lacking so that Lean exploration is still needed in the management aspect. This research will examine the effect of LMS, LWRT on LBR. This research was conducted on 30 companies in industrial centers in Indonesia, and the data were processed using the Structural Equation Model method. It was found that LMS has no significant effect on LBR, but LMS has a significant effect on LWRT, while LWRT has a significant effect on LBR. In detail, LBR variation of 78.8% is simultaneously influenced by LMS and LWRT, 21.2% is influenced by other variables. While 72.7% LWRT variation is influenced by LMS variation, and 27.3% is influenced by other variables. This result confirms Bergmiller’s research (2009) that LMS has a significant effect on LBR through LWRT for the manufacturing industry in Indonesia.

This paper presents the concept and methodology for the designing of a “tree-shaped” production line. The concept is a result of the search for production unit organization that meets the Lean Production assumptions, i.e. focusing on lead time (throughput time) shortening with simultaneous ability of use in conditions of varied product range. The varied product range characterized by lower technological-organizational similarity when compared to “Ushaped” units typical for Lean Production. The paper presents an algorithm for the designing of a “tree-shaped” production line and examples of its application. The designed unit underwent evaluation according to the criteria preferred by Lean Manufacturing experts. The designed production unit achieved results confirming the effectiveness of the proposed concept for the analysed sets of input data on the product range and production capacities.

The aim of this paper is to identify lean management instruments used to implement strategic

objectives related to the creation and retention of value in the area of value networks while

redefining the business model of service enterprises on the example of hotels. In relation

to the objective, a survey was conducted using the questionnaire method with the use

of Computer Assisted Web Interview technique, using a self-developed questionnaire. The

survey was carried out between February and May 2020 among 421 representatives of hotel

service companies operating in the three, four and five-star standard. In order to verify

the assumptions between the surveyed features, statistical inferences were used using the

Statistica programme. The research results may provide inspiration for the implementation

of lean management concept in the area of redefining business models conducive to value

creation. The issues presented in the paper are an attempt to fill the gap indicating practical

experience related to the use of lean management instruments in the hotel services sector

and their effectiveness in the process of redefining business models and value creation.

One of the main challenges to solve in an Industry 4.0 context for manufacturing leaders worldwide is increasing product and value-stream complexity. In this paper we present a standardized visualization methodology through multichannel plots applied to complex organizational design network configurations. Combining network theory and strategic lean management oriented organizational design through Hoshin Kanri Forest technology, this approach is expected to allow scholars and organizational leaders to systematically visualize strategic organizational design KPI (key performance indicator) dynamic states and hence significantly reduce KPI interpretation complexity. An example is briefly shown for explanatory purposes

The application of the 5S methodology to warehouse management represents an important

step for all manufacturing companies, especially for managing products that consist of

a large number of components. Moreover, from a lean production point of view, inventory

management requires a reduction in inventory wastes in terms of costs, quantities and time

of non-added value tasks. Moving towards an Industry 4.0 environment, a deeper understanding

of data provided by production processes and supply chain operations is needed:

the application of Data Mining techniques can provide valuable support in such an objective.

In this context, a procedure aiming at reducing the number and the duration of picking

processes in an Automated Storage and Retrieval System. Association Rule Mining is applied

for reducing time wasted during the storage and retrieval activities of components

and finished products, pursuing the space and material management philosophy expressed

by the 5S methodology. The first step of the proposed procedure requires the evaluation

of the picking frequency for each component. Historical data are analyzed to extract the

association rules describing the sets of components frequently belonging to the same order.

Then, the allocation of items in the Automated Storage and Retrieval System is performed

considering (a) the association degree, i.e., the confidence of the rule, between the components

under analysis and (b) the spatial availability. The main contribution of this work is

the development of a versatile procedure for eliminating time waste in the picking processes

from an AS/RS. A real-life example of a manufacturing company is also presented to explain

the proposed procedure, as well as further research development worthy of investigation.

Lean thinking and Industry 4.0 have been broadly investigated in recent years in intelligent manufacturing. Lean Production is still one of the most efficient industrial solutions in business and research, despite being implemented for a long time. On the other hand, Industry 4.0 has been introduced referring to the fourth industrial revolution. This study aims to analyze the combination of both Industry 4.0 and Lean production practices through a systematic literature review from a Lean Automation perspective. In this field, 189 articles are examined using VOSviewer for cluster analysis. Then, a more detailed analysis is provided to explore how Industry 4.0 and Lean techniques are integrated from a practical perspective. Results highlighted Big Data Analysis and Value Stream Mapping as the most common techniques, also emphasizing a growing trend toward new publications. Nevertheless, few practical applications are identified in the literature highlighting six gaps in the correlation of LA practices.