The market of consumer goods requires nowadays quick response to customer needs. As a consequence, this is transferred to the time restrictions that the semi-finished product manufacturer must meet. Therefore the cost of manufacturing cannot determine how production processes are designed, and the main evaluation function of manufacturing processes is the response time to customers’ orders. One of the ideas for implementing this idea is the QRM (Quick Response Manufacturing) production organization system. The purpose of the research undertaken by the authors was to develop an innovative solution in the field of production structure, allowing for the implementation of the QRM concept in a Contract Manufacturer, which realizes its tasks according to engineering-to-order (ETO) system in conditions defined as High Mix, Low Volume, High Complexity. The object of the research was to select appropriate methods for grouping products assuming that certain operations will be carried out in traditional but well-organized technological and/or linear cells. The research was carried out in one of the largest producers of sheet metal components in Europe. Pre-completed groupings for data obtained from the company had indicated that – among the classical methods – the best results had been given by the following methods: King’s Algorithm (otherwise called: Binary Ordering, Rank Order Clustering), k-means, and Kohonen’s neural networks. The results of the tests and preliminary simulations based on the data from the company proved that the implementation of the QRM concept does not have to be associated with the absolute formation of multi-purpose cells. It turned out that the effect of reducing the response time to customer needs can be obtained by using hybrid structures that combine solutions characteristic of cellular systems with traditional systems such as a technological, linear, or mixed structure. However, this requires the application of technological solutions with the highest level of organization.

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

Industry 4.0 is expected to provide high quality and customized products at lower costs by increasing efficiency, and hence create a competitive advantage in the manufacturing industry. As the emergence of Industry 4.0 is deeply rooted in the past industrial revolutions, Advanced Manufacturing Technologies of Industry 3.0 are the precursors of the latest Industry 4.0 technologies. This study aims to contribute to the understanding of technological evolution of manufacturing industry based on the relationship between the usage levels of Advanced Manufacturing Technologies and Industry 4.0 technologies. To this end, a survey was conducted with Turkish manufacturers to assess and compare their manufacturing technology usage levels. The survey data collected from 424 companies was analyzed by machine learning approach. The results of the study reveal that the implementation level of each Industry 4.0 technology is positively associated with the implementation levels of a set of Advanced Manufacturing Technologies.

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.

Recent rapid developments in information and network technology have profoundly influenced manufacturing research and its application. However, the product’s functionality and complexity of the manufacturing environments are intensifying, and organizations need to sustain the advantage of huge competitiveness in the markets. Hence, collaborative manufacturing, along with computer-based distributed management, is essential to enable effective decisions and to increase the market. A comprehensive literature review of recent and state-of-the-art papers is vital to draw a framework and to shed light on the future research avenues. In this review paper, the use of technology and management by means of collaborative and cloud manufacturing process and big data in networked manufacturing system have been discussed. A systematic review of research papers is done to draw conclusion and moreover, future research opportunities for collaborative manufacturing system were highlighted and discussed so that manufacturing enterprises can take maximum benefit.

Lean has established itself as the primordial approach to obtain operational excellence. Its simple and intuitive techniques focus on reducing lead time through continuous improvement, involving all levels of employees in the organization. However, the rate of successful implementations has remained low. This paper contributes to the understanding of continuous improvement in a Lean context, by analyzing a database of almost 10.000 improvement actions, from 85 companies, covering the time frame 2010–2018. It discusses categories of actions, their impact and cost, as well as key characteristics of the companies. It proposes an objective criterion to identify “success” and “failure” in Lean implementation and tries to link these to operational results. It is probably the first time an analysis of this magnitude on the subject has been performed.

High business competition demands business players to improve quality. The Six Sigma

with DMAIC phases is a strategy that has proven effective in improving product and service quality. This study aims to find the consistency of DMAIC phases implementation and

analyze the objective value in Six Sigma research. By using a number of trusted article

sources during 2005 until 2019, this research finds that 72% research in manufacturing industry consistently implemented DMAIC roadmap especially in case study research type

for problem-solving, while service industry pointed out the fewer number (60%). The causes

of variations and defective products in the manufacturing industry are largely caused by

a 4M 1E factor, while in service industry are caused by human behavior, and it’s system

poorness. Both manufacturing & service industry emphasized standardization & monitoring to control the process which aimed at enhancing process capability and organization

performance to increase customer satisfaction.

Today’s manufacturing environment is highly uncertain, and it is continuously changing. It

is characterized by shorter life cycles of products and technologies, shorter delivery times, an

increased level of customization at the price of a standard product, increased product variety,

quality as well as demand variability and intense global competition. Academicians, as well as

practitioners, agree that uncertainty will continue to grow in the twenty-first century. To deal

with the uncertainties in demand variation and production capacity a manufacturing system

is required which can be easily reconfigured when there is a need at low cost. A reconfigurable

manufacturing system is such a type of system.

In the present work, the concept of the reconfigurable manufacturing system has been discussed

and reviewed. It has been compared with dedicated systems and flexible manufacturing

systems. Part family formation and barriers of reconfiguration also have been discussed.

This work is an attempt to contribute to the conceptual systematization of the reconfigurable

manufacturing system and reconfigurability by synthesizing the vast literature available after

a systematic review.

With the increasing demand of customisation and high-quality products, it is necessary for

the industries to digitize the processes. Introduction of computers and Internet of things

(IoT) devices, the processes are getting evolved and real time monitoring is got easier.

With better monitoring of the processes, accurate results are being produced and accurate

losses are being identified which in turn helps increasing the productivity. This introduction

of computers and interaction as machines and computers is the latest industrial revolution

known as Industry 4.0, where the organisation has the total control over the entire value chain

of the life cycle of products. But it still remains a mere idea but an achievable one where IoT,

big data, smart manufacturing and cloud-based manufacturing plays an important role. The

difference between 3rd industrial revolution and 4th industrial revolution is that, Industry

4.0 also integrates human in the manufacturing process. The paper discusses about the

different ways to implement the concept and the tools to be used to do the same.

One of the strategic decisions of any organization is decision making about manufacturing

strategy. Manufacturing strategy is a perspective distinguishing a company from other

present companies in that industry and creates a kind of stability in decisions and gives a special

direction to organizational activities. SIR (SUPERIORITY& INFERIORITY Ranking)

method and their applications have attracted much attention from academics and practitioners.

FSIR proves to be a very useful method for multiple criteria decision making in fuzzy

environments, which has found substantial applications in recent years. This paper proposes

a FSIR approach based methodology for TOPSIS, which using MILTENBURG Strategy

Worksheet in order to analyzing of the status of strategy of the Gas Company. Then formulates

the priorities of a fuzzy pair-wise comparison matrix as a linear programming and

derives crisp priorities from fuzzy pair-wise comparison matrices

Manufacturing levers (Alternatives) are examined and analyzed as the main elements of

manufacturing strategy. Also, manufacturing outputs (Criteria are identified that are competitive

priorities of production of any organization. Next, using a hybrid approach of FSIR

and TOPSIS, alternatives (manufacturing levers) are ranked. So dealing with the selected

manufacturing levers and promoting them, an organization makes customers satisfied with

the least cost and time.

The modern companies, which are competing on product market, need to use innovative solutions, in order to become potential leaders. One of the modernization methods is rearrangement of organizational structure and redistribution of competence. The article describes the Advanced Manufacturing Engineering Department in production plant, which is an innovative initiative in worldwide organizational management. Some aspects including AME application in plant processes are highlighted. Some advanced techniques are presented. In the article summary, perspectives for the development of AME are included.

This paper presents the results of a metrological analysis of the additively manufactured (AM) copies of a complex geometrical object, namely the fossil skull of Madygenerpeton pustulatum. This fossil represents the unique remains of an extinct “reptiliomorph amphibian” of high importance for palaeontological science. For this research, the surface was scanned and twelve different copies were 3D-printed using various devices, materials, and AM techniques. The same digitized model was used as a reference to compare with the surfaces obtained by Mitutoyo Coordinate Measuring Machine (CMM) CRYSTA-Apex S 9166 for each copy. The fidelity of the copies was assessed through statistical analysis of the distances between compared surfaces. The methodology provided a good background for the choice of the most accurate copies and the elimination of the less accurate ones. The proposed approach can be applied to any object of complex geometry when reproduction accuracy is to be assessed.

Computational intelligence (CI) can adopt/optimize important principles in the workflow of 3D printing. This article aims to examine to what extent the current possibilities for using CI in the development of 3D printing and reverse engineering are being used, and where there are still reserves in this area. Methodology: A literature review is followed by own research on CI-based solutions. Results: Two ANNs solving the most common problems are presented. Conclusions: CI can effectively support 3D printing and reverse engineering especially during the transition to Industry 4.0. Wider implementation of CI solutions can accelerate and integrate the development of innovative technologies based on 3D scanning, 3D printing, and reverse engineering. Analyzing data, gathering experience, and transforming it into knowledge can be done faster and more efficiently, but requires a conscious application and proper targeting.

Major manufactures are moving towards a sustainability goal. This paper introduces the results of collaboration with the leading company in the packaging and advertising industry in Germany and Poland. The problem addresses the manufacturing planning problem in terms of minimizing the total cost of production. The challenge was to bring a new production planning method into cardboard manufacturing and paper processing which minimizes waste, improves the return of expenses, and automates daily processes heavily dependent on the production planners’ experience. The authors developed a module that minimizes the total cost, which reduces the overproduction and is used by the company’s manufacturing planning team. The proposed approach incorporates planning allowances rules to compromise the manufacturing requirements and production cost minimization.

The paper presents the technology and organization of the artistic cast production. On the basis of the actual cast production system, the

manufacturing process was shown, in particular sand–piece moulding, which is a very important process and a time-consuming part of the

entire manufacture of the casts. The current state of the production process as well as the organization of the work and production

technology were analysed with the use of methods and techniques of production improvement, the Lean Manufacturing concept and

computer systems. The results of the analysis and studies were shown with use of schemes and graphs of the layout of the production

resources, a flow chart of the production process, value stream mapping, and a costs table for the production and modernization of the

moulding stage. The work has shown that there are possibilities to improve the artistic cast production system. This improvement leads to

increased productivity, lower production costs of artistic casts and increased competitiveness of the foundry.

Additive manufacturing (AM) is a process that joins similar or dissimilar materials into application-oriented objects in a wide range of sizes and shapes. This article presents an overview of two additive manufacturing techniques; namely Laser metal deposition (LMD) and Wire arc additive manufacturing (WAAM). In LMD, metallic powders are contained in one or more chambers, which are then channelled through deposition nozzles. A laser heats the particles to produce metallic beads, which are deposited in layers with the aid of an in-built motion system. In WAAM, a high voltage electric arc functions as the heat source, which helps with ensuring deposition of materials, while materials in wire form are used for the feedstock. This article highlights some of the strengths and challenges that are offered by both processes. As part of the authors’ original research work, ­Ti-6Al-4V, Stainless steel 316L and Al-12Si were prepared using LMD, while the WAAM technique was used to prepare two Al alloys; Al-5356 and CuAl8Ni2. Microstructural analysis will focus on similarity and differences in grains that are formed in layers. This article will also offer an overall comparison on how these samples compare with other materials that have been prepared using LMD and WAAM.

The purpose of the present paper was to investigate the effect of shot peening on the condition of the surface layer and abrasion resistance of specimens made of Ti-6Al-4V titanium alloy produced by Direct Metal Laser Sintering (DMLS) process. The specimens have been produced by means of EOSINT M280 system dedicated for laser sintering of metal powders and their surfaces have been subjected to the shot peening process under three different working pressures (0.2, 0.3 and 0.4 MPa) and by means of three different media i.e. CrNi steel shot, crushed nut shells and ceramic balls. The specimens have been subjected to profilometric analysis, to SEM examinations, microhardness tests and to tribological tests on ball-on-disc stand in Ringer fluid environment. The general results of all tests indicate to favourable effect of shot peening process on the hardness and tribological performance of titanium alloy.

This article intends to justify the gap in the research of similarity coefficient driven approaches

and cell formation problems (CFP) based on ratio data in cellular manufacturing systems

(CMS). The actual implication of ratio data was vaguely addressed in past literature, which

has been corrected recently. This research considered that newly projected CFP based on

ration data. This study further revealed the lack of interest of researchers in investigation for

an appropriate and improved similarity coefficient primarily for CFP based on ratio data.

For that matter a novel similarity coefficient named as Generalized Utilization-based Similarity

Coefficient (GUSC) is introduced, which scientifically handles ratio data. Thereafter

a two-stage cell formation technique is adopted. First, the proposed GUSC based method

is employed to obtained efficient machine cells. Second, a novel part allocating heuristic is

proposed to obtain effective part families. This proposed approach is successfully verified on

the test problems and compared with algorithms based on another similarity coefficient and

a recent metaheuristic. The proposed method is shown to obtain 66.67% improved solutions.

One of the key factors of a competitive economy is creating a strong, internationally competitive SME sector. This essay is based on the fact that management tools used in the SME sector are insufficient. With the development of these tools, the competitiveness of companies could improve. According to the literature, using lean thinking has a positive influence on the company’s effectiveness, and also proved that lean approach can be successfully extended out of the car industry, into the limitedly resourced SME sector, too. Even though the topic of lean manufacturing is analysed by many studies, there is a lack of papers dealing with its usage in the SME sector. The originality of this paper lies in analysing the current status of using lean manufacturing practices among the Hungarian SMEs operating in the manufacturing industry. The paper includes an examination about how deeply the elements of lean thinking are present in the Hungarian SME sector, how large the development reserves are, and whether there is a difference between the usage of lean practices. A structured questionnaire was used for data collection. SMEs’ representatives, mostly CEOs and managers from the Hungarian manufacturing industry participated in the survey. The sample contained 128 observations. The study has two control variables, which are the size of the company and the relation to the lean management. The survey brought the following results. First of all, it shows that the level of using lean is low among the Hungarian SMEs. Furthermore, customer orientation is a key factor in the sector, however, there are considerable possibilities for progress by the inner processes and the handling and involvement of the suppliers. Firstly, a good basis to increase the effectiveness could be the creation of thinking in processes influencing the supply chain. Secondly, the development of the leadership and the involvement of the employees at some level are also significant. Key findings is that without state incitement and the involvement of outside experts, progress cannot be expected to spread on a broad scope. The background of the research method was created to fit the available literature and to capable to be used in other countries, too. Moreover, this way the available information can be expanded with a regional dimension, in case further studies are going to be made.

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 article summarizes the arguments and counterarguments within the scientific discussion on identifying the enterprise’s state to evaluate its effectiveness and optimize the

target functions in solving enterprise development problems. The proposed scientific and

methodological approach to modeling the enterprise development management system under decentralization conditions and its practical implementation makes it possible to determine the dominant development parameters of manufacturing enterprises that influence

the United Territorial Community and to timely track the impulses and space of the United Territorial Community state, taking into account the PS state as parameters for its

development. The proposed analysis of the Production System state within the United

Territorial Community framework and evaluating its development dynamics shows the necessity of forming a system of generalized vector-scalar, situationally oriented indicators.

In the era of Industry 4.0, the automation of processes in the life cycle of a product seems

to be a necessity. Although programming CNC machines with CAM systems make it possible,

it is necessary to effectively acquire knowledge about the programming process and

technological requirements for effective automation. The paper presents a method for decomposition

of knowledge about the CNC machine programming process based on acquiring

knowledge from various sources, both from technologists as well as on the basis of analysis

of archival CNC control programs. To decompose the programming process, it is proposed

to apply the knowledge model described by various attributes. Verification of the method

is shown in the process of knowledge decomposition for manufacturing special production

tooling.

A robust manufacturing sector is imperative for achieving sustainable and inclusive development.

Also, in the Indian context, Micro, Small and Medium Enterprises (MSMEs) are

of vital importance due to their contribution to GDP, exports and employment. Indian

Government has launched many schemes to vitalize and improve the competitiveness of

Manufacturing MSMEs. ‘Lean Manufacturing Competiveness Scheme’ (LMCS) is a huge

step aimed to act as a catalyst for lean adoption by Indian MSMEs. This paper uses SAP

LAP framework to address critical questions regarding lean adoption by Indian manufacturing

MSMEs in the context of the government scheme ‘LMCS’. The study adds to the

existing body of knowledge on lean manufacturing that emphasizes on the importance of

soft issues while implementing lean. It also benefits the stakeholders by suggesting suitable

actions that can be taken to further improve the competitive priorities of MSMEs.

In order to assess the challenges and needs of Austrian companies with respect to current

business and technological developments, a regular well-researched compilation of empirical

data of the Austrian manufacturing industry is necessary. Hence, a panel of 104 decisionmakers

(owners, CEOs, managing directors and plant managers) from leading Austrian

industrial companies was assembled in form of an “industry panel” to investigate current

issues of production work in Austria by means of a survey.

In order to allow for a longitudinal study, it is planned to survey the same group of people

every year; hence the instrument of an annual panel-survey was chosen. To date the panel

consists of 104 leaders from different Austrian or international companies with at least one

factory location in Austria. The panel was assembled first in 2018/2019 and the administered

survey contained 23 questions. The actual questions comprise topics that concern the current

economic situation and future expectations, operational issues with respect to delivery

time, product variability and demand fluctuations, as well as questions relating to innovation,

automation and the application of current technological developments (i.e. assistance

systems, machine learning, etc.) in manufacturing. This paper presents the survey results

and conclusions of the 2019 panel on production work in Austria.