This study provides a systematic review of the existing academic literature describing the
key components of eMaintenance. The current literature is reviewed by utilizing a number of
academic databases including Scopus, SpringerLink and ScienceDirect, and Google Search is
used to find relevant academic and peer-reviewed journal articles concerning eMaintenance.
The literature describes eMaintenance as an advanced maintenance strategy that takes advantage
of the Internet, information and communication technologies, wireless technologies
and cloud computing. eMaintenance systems are used to provide real time analyses based
on real time data to offer a number of solutions and to define maintenance tasks. The collection
and analysis of appropriate maintenance and process data are critical to create robust
‘maintenance intelligence’ and finally improvements in manufacturing costs, safety, environmental
impact, and equipment reliability. This paper describes how the scientific discussion
on eMaintenance has expanded significantly during the last decade, creating a need for an
up-to-date review. As a conclusion, three research gaps in the area of eMaintenance are
identified, including evaluating the benefits of eMaintenance, agreeing on a
Studies linking the use of lean practices to company performance have been increasing as
markets are becoming more competitive and companies are eager for reducing waste and
therefore implementing the Lean Management (LM) philosophy to improve performance.
However, results from these studies have found various and different impacts and some light
is needed. Extant literature was reviewed and, to achieve the research objective, a metaanalysis
of correlations was carried out. The obtained results suggest a positive relationship
between some lean practices and performance measures. Furthermore, the presence of moderators
influencing the relationship between lean practices and performance outcomes is
highlighted in our results. To our best knowledge, this is the first research that proposes
a comparison of results from primary studies on Lean implementation, by analysing the
linear relationship between lean practices and enterprise performance. It fills this gap and
therefore represents an important contribution.
The presented method is constructed for optimum scheduling in production lines with parallel
machines and without intermediate buffers. The production system simultaneously
performs operations on various types of products. Multi-option products were taken into
account – products of a given type may differ in terms of details. This allows providing for
individual requirements of the customers. The one-level approach to scheduling for multioption
products is presented. The integer programming is used in the method – optimum
solutions are determined: the shortest schedules for multi-option products. Due to the lack
of the intermediate buffers, two possibilities are taken into account: no-wait scheduling,
possibility of the machines being blocked by products awaiting further operations. These two
types of organizing the flow through the production line were compared using computational
experiments, the results of which are presented in the paper.
In the article, the significance and essence of management of intelligent manufacturing in
the era of the fourth industrial revolution has been presented. The current revolution has
a large impact on the operation of the company. Through the changes resulting from the
application of modern technologies, production processes are also undergoing revolutions,
which results in changes in such indicators of business development. Management of intelligent
manufacturing is also a challenge for socially responsible activities; due to solutions of
Industry 4.0, enterprises directly and indirectly influence environmental protection, which
results in benefits for all mankind. In the article, the analysis and assessment of management
of intelligent manufacturing, using modern technologies during the production process,
has been carried out, with particular emphasis on the components of management such as:
monitoring, control, autonomy, optimization. Moreover, the impact of the above components
of management on changes in the following indicators (KPI – Key Performance Indictors)
has been evaluated, i.e. (1) quality, (2) rapidity of the production process implementation,
(3) performance and (4) productivity, (5) decrease in waste generated during the technological
process and (6) amount of consumed electricity. For the purposes of conducting the
research, a case study has been used, developed due to the information shared by the company
manufacturing machinery and equipment for the polymer processing industry, in which
intelligent solutions of Industry 4.0 are being applied. The presented article is a significant
contribution to the current development of knowledge in the field of implementing Industry
4.0 solutions for polymer processing. The article is a combination of theoretical and practical
knowledge in the field of management and practical industrial applications. It refers to the
most current research trends.