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.

Up to date, workload and worker performance in Small Medium-sized Enterprise (SMEs)

was assessed manually. KESAN (Kansei Engineering-based Sensor for Agroindustry) was

developed as a tool to assess worker workload and performance. The latest prototype of

KESAN was established. As the final step prior to the full-scale mass production, an industrial

design was required and must be designed based on the validation to user needs. This

research proposed an industrial design for mass production of KESAN using Kano model

and Quality Function Deployment (QFD). The user needs was extracted from attributive

analysis of Kano model. The matrix of House of Quality (HOQ) was utilized to connect

the user needs and technical requirement. The research result validated Thirteen (13) user

need attributes. The most important attribute was desktop application as an integrated

decision support system. Fourteen (14) technical requirement attributes were identified to

fulfil the user needs. Finally, a prototype was developed based on product final specification

and prioritized technical requirements.

The relatively limited application of lean in the food process industries has been attributed to

the unique characteristics of the food sector i.e. short shelf-life, heterogeneous raw materials,

and seasonality. Moreover, barriers such as large and inflexible machinery, long setup time,

and resource complexity, has limited the implementation and impact of lean practices in

process industries in general. Contrary to the expectations in the literature, we bring in this

paper a successful experience of lean implementation in a company of the food-processing

sector. By focusing on two lean tools (VSM and SMED), the company reduced changeover

time by 34%, and increased the production capacity of the main production line by 11%.

This improvement enabled the company to avoid the use of temporary workers by extending

the worktime of its workforce during peak months. Moreover, the reduction of setup time

avoided the use of large lot size in production, which, in turn, reduced the total cycle time

of production and the incidence of quality problems.

Labor absenteeism is a factor that affects the good performance of organizations in any

part of the world, from the instability that is generated in the functioning of the system.

This is evident in the effects on quality, productivity, reaction time, among other aspects.

The direct causes by which it occurs are generally known and with greater reinforcement

the diseases are located, without distinguishing possible classifications. However, behind

these or other causes can be found other possible factors of incidence, such as age or sex.

This research seeks to explore, through the application of neural networks, the possible

relationship between different variables and their incidence in the levels of absenteeism. To

this end, a neural networks model is constructed from the use of a population of more than

12,000 employees, representative of various classification categories. The study allowed the

characterization of the influence of the different variables studied, supported in addition to

the performance of an ANOVA analysis that allowed to corroborate and clarify the results

of the neural network analysis.

Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.

The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed.

We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials.

Letters to the Editor-in-Chief are highly encouraged.

Performance measurement system in supply chain management (SCM) has been receiving increasing

attention by business organizations as a way to evaluate efficiency in supply chain

activities. Assessing the performance of supply chain uncovers the gap between planning

and actual performance as to trace the potential problems thus ascertain necessary areas

for improvement. This research aims to investigate the application of performance measurement

system in SCM as well as exploring its relationship with organization’s performance

among Malaysian manufacturing firms. By utilizing the questionnaire method, respondents

involved were requested to indicate the extent to which they use a number of 24 selected

performance measures that are related to SCM. The results show that the majority of the

observed manufacturing firms utilize specific performance measurement tools in evaluating

the supply chain performance. The current performance measurement techniques, the Balanced

Score Card is adopted by around a quarter of the total responding firms followed

by Supply Chain Operations References Model – SCOR, which attracts total users of only

a fifth of the total respondents. In particular, performance measures under customer service

category recorded the highest number of usage followed by cost-based performance measures

and operations management. The results of this investigation also unveil few major points

that are important to be highlighted. Firstly, the obtained outcomes of this study bring to

light the significant relationships between the utilization of supply chain performance measures

under customer service, operations management and organizational performance. In

addition, this study discovered a significant correlation between the size of the organization

and the extent of use of supply chain performance measures and how these two variables

positively correlated. Lastly, the findings also suggested that the performance measures for

SCM has been playing a crucial role in enhancing the performance of the organizations and

is increasingly operated as the firms grow in size. Based on the brief highlighted points listed

above, it is not an exaggeration to say that this research contributes new information to the

body of knowledge in performance measurement system in SCM and its associations with

organizational performance.

The main purpose of this article is to present an author’s methodology of production levelling

and to show the impact of levelling on the time during which the product passes

through the process and on staff performance. The article presents the analysis of literature

concerning the method of improving the production process, especially taking production

levelling into consideration. The authors focussed on the definition and methodologies of

production levelling. A diagram of interrelations showing determinants and efficiency measures

of production levelling as well as an author’s production levelling methodology have

been presented. An example of the implementation of production levelling in one of the departments

of a company manufacturing surgical instruments has also been shown. Analysis

of the current state, stages of implementation and end effects have been presented. Attention

was focussed on the time during which the product passes through the process and on staff

performance.

Seasonality is a function of a time series in which the data experiences regular and predictable

changes that repeat each calendar year. Two-stage stochastic programming model

for real industrial systems at the case of a seasonal demand is presented. Sampling average

approximation (SAA) method was applied to solve a stochastic model which gave a productive

structure for distinguishing and statistically testing a different production plan. Lingo

tool is developed to obtain the optimal solution for the proposed model which is validated

by Math works Matlab. The actual data of the industrial system; from the General Manufacturing

Company, was applied to examine the proposed model. Seasonal future demand

is then estimated using the multiplicative seasonal method, the effect of seasonality was

presented and discussed. One might say that the proposed model is viewed as a moderately

accurate tool for industrial systems in case of seasonal demand. The current research may

be considered a significant tool in case of seasonal demand. To illustrate the applicability of

the proposed model a numerical example is solved using the proposed technique. ANOVA

analysis is applied using MINITAB 17 statistical software to validate the obtained results.

The difficulty of innovation risk assessment makes it necessary to use a multi-criteria analysis.

Innovative projects are related to unstructured problems and the uncertainty, therefore,

the use of fuzzy logic in the innovation risk assessment is analyzed. This paper proposes

a method of determining the weights of criteria in order to innovation risk assessment. The

weights are determined by 5 general criteria and 14 detailed criteria of innovation risk assessment.

The proposed method is an extension of the fuzzy AHP method. The extension

consists in taking into consideration the group decision-making approach with experts’ psychological

conditions. The groups of experts have been chosen based on an elaborated form.

The form makes it possible to characterize the persons within the scope of different psychological

conditions. The proposed method provides objective and rational decision-making.

The paper presents also a comparison of results with the fuzzy AHP method without the

group decision making. The weights obtained by the proposed method are more diversified

and bring out the most important criteria.

This study presents a customized root cause analysis approach to investigate the reasons,

provide improvements measures for the cost overruns, and schedule slippage in papermachine-

building projects. The proposed approach is an analytical-survey approach that

uses both actual technical data and experts’ opinions. Various analysis tools are embedded

in the approach including: data collection and clustering, interviews with experts, 5-Whys,

Pareto charts, cause and effect diagram, and critical ratio control charts. The approach was

implemented on seven projects obtained from a leading international paper machine supplier.

As a result, it was found that the main causes behind cost and schedule deviations

are products’ related; including technical accidents in the Press section, damaged parts, design

issues, optimization of the machine and missing parts. Based on the results, prevention

measures were perceived.

The operation of thermal devices and installations, in particular heat exchangers, is associated

with the formation of various deposits of sediments, forming the boiler scale. The

amount of precipitate depends on the quality of the flowing liquids treatment, as well as

the intensity of the use of devices. There are both mechanical and chemical treatment methods

to remove these deposits. The chemical methods of boiler scale treatment include the

cleaning method consisting in dissolving boiler scale inside heat devices. Worked out descaling

concentrate contains phosphoric acid (V) and the components that inhibit corrosion,

anti-foam substances, as well as anti-microbial substances as formalin, ammonium chloride,

copper sulphate and zinc sulfate. Dissolution of the boiler scale results in the formation of

wastewater which can be totally utilized as raw materials in phosphoric fertilizer produc

Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.

The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed.

We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials.

Letters to the Editor-in-Chief are highly encouraged.

Agile Project Management is a topic that has become popular both in business and academia, since the publication of the Agile Manifesto – a historic landmark in this subject. In the next 20 years, there was a relevant scientific production that must be analyzed to provoke reflection about the knowledge built up in this period. In this sense, this study aims to analyze the relevant scientific literature on Agile Project Management through a systematic review and a bibliometric analysis of articles published in scientific journals with Digital Object Identifier, in English, from the Web of Science and Scopus databases, from 2001 to 2021. The research results enable us to gain insights into the characteristics of this knowledge domain, regarding its volume and evolutionary trend, main contributors (i.e. scientific journals, authors, and their affiliations), main studies, methods used, and its central thematic axes.

This study uses statistical quality control (SQC) and overall equipment effectiveness (OEE) to examine quality at a porcelain production firm. The study is motivated by the most frequently broken machines in 2019, is the Jigger 01 machine. This paper aims to evaluate the machine’s effectiveness using the OEE method. The OEE determines the scope of the problem to be solved using the SQC method. The average OEE value in 2019 was 70%. Based on the SQC method, the product defect produced is still under control. However, the average defect is still above the company’s tolerance limit of 10%. Consequently, this study offers enhancements utilizing the Failure Mode Effect Analysis (FMEA) technique. The results indicate that human resources and machines caused defective products. This paper contributes to providing several improvements that the company can apply to maximize its quality control analysis. After implementing the improvement, the OEE value increases to 74%.

Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.

The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed.

We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials.

Letters to the Editor-in-Chief are highly encouraged.

The fourth industrial revolution has resulted in technology advancements in the manufacturing industry. However, the innovation potential embedded in these technologies should be unlocked by a viable application, i.e., the business model (BM). The BM as a holistic concept featuring different interacting elements is thus emerging as a promising vehicle for innovation. Current BM research describes the entire domain but lacks depth in the characterization of its individual components. This paper investigates the available manufacturing literature through the lens of the BM concept performing a scientometric analysis. The results are presented in a relational framework that provides an in-depth characterization of the manufacturing element of the BM and highlights identified connections that link the BM components. This is the basis for tools that will support firms in developing manufacturing portfolios aligned with their strategic goals.

With continuous and rapid change in both technology and businesses due to climate change and governments regulations, Green Supply Chain Management (GSCM) is receiving increasing attentions during last two decades. GSCM refers to the abilities of businesses to enhance operations and sustain environment at the same time and efficiently. In this paper, a comprehensive review of GSCM development and applications is conducted. This review aims to explore the recent developments of GSCM and necessity of adoption GSCM applications in businesses to insure sustainable development. First, a descriptive analysis of 796 paper adopted from Scopus database was conducted to review research on GSCM. Next, a bibliometric analysis of 235 paper was conducted to determine the recent trends and areas of GSCM and related keywords by using VOSviewer software. Then, a content analysis was carried out of 53 review papers by adopting WordStat software to analyze the impact of GSCM on related subjects and trends of GSCM. Finally, a summary analysis of GSCM advantages and challenges was conducted based on fundamental GSCM’s objectives. Results reveal that researches on GSCM are in upward curve with limitations in implementing GSCM applications due to high cost, and lack of sufficient experiences. Results also reveal positive moderate correlation of GSCM with environment, performance, sustainability and management practices indicating the limited implementation of GSCM applications. To further explore these limitations, this study summarized the recent challenges and future potential directions of GSCM in both businesses and environments.

Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.

The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed.

We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials.

Letters to the Editor-in-Chief are highly encouraged.

Organisations have to take into account rapid, non-linear changes in their environment that build pressure on the company‘s development strategy. Therefore, one of the key challenges and paradoxes is to how maintain mutual coherence between different areas of the organisation and simultaneously leverage being ambidextrous so as to continue with exploration and exploitation activities. The main goal of this paper is to present research results on the relation between strategic coherence and company ambidexterity.
Strategic coherence is a proprietary concept allowing for measurement of the balance between the vertical and horizontal adjustment of an organisation. Vertical adjustment is the relation between strategy and the elements of the business model measured by: 1) the cascading of goals, 2) feedback on matching elements of the business model according to strategy, and 3) control over financial results and strategy implementation. Horizontal adjustment refers to matching the business model components measured by: 1) creating value, 2) capturing value, and 3) creating a synergy effect) Meanwhile, ambidexterity is determined by four areas: 1) company goals, 2) products, 3) market and 4) competitive advantage for both exploration and exploitation activities. The research survey was conducted with the use of the CATI method. Altogether, 400 medium-sized and large Polish companies were included in the study. To calculate the dependencies, the Pearson correlation coefficient was applied. The companies studied achieved similar results in terms of strategic coherence dimensions, as the vertical adjustment was 6.47, and the horizontal was 6.29 on a scale of 1–10. Meanwhile, in terms of ambidexterity, the companies achieved a moderate level, with the average value for exploration being 4.26, and that for exploitation 4.51 on a scale from 1 to 7. Based on correlation analysis, the relation between both variables has the shape of an inverted “U” with the most favourable point for ambidexterity at the “high strategic coherence” level. This study is a comprehensive guide for practitioners, and presents development guidelines for companies. The value of this research is an empirically validated framework that describes relations based on a dynamic balance between strategic coherence and two types of adjustment in the area of regulation – vertical and horizontal, as well as ambidexterity with two types of activity in the area of operations: exploration and exploitation. This study is unique and explores uncharted areas of strategic management.

The Controlled Atmosphere Brazing (CAB) process together with NOCOLOKr flux is associated with the occurrence of potassium fluoroaluminate residue inside the cooler. Excess of this flux residue is known to cause gelation of the coolant, which deteriorates the efficiency of the cooler. The flux residue amount is most often measured via Atomic Absorption Spectroscopy (AAS), in accordance with DIN ISO 9964-3. This is a time-consuming measurement that requires the use of specialized equipment and costly solvents. The following article presents two innovative methods for flux residue measurement after CAB process. They include Scanning Electron Microscopy (SEM) with Energy-Dispersive X-ray Spectroscopy (EDS) and Reflected Light Microscopy (RLM) with Differential Interference Contrast (DIC) module. The accuracy of these methods has been compared to the reference AAS method to evaluate their potential as alternative, less expensive, and quicker measurement methods for determining the quantity of flux residue.

Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.

The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed.

We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials.

Letters to the Editor-in-Chief are highly encouraged.

The article explores megatrends in management, related to the transition to digital technologies in all spheres of the economy and production in the COVID-19 pandemic. The main contribution to the analysis of the current state of digitalization HR in business. The possibilities of a set of processes and methods of interaction with information in the formation of a strategy of people’s management, are investigated. This is achieved through the use of integrated mobile applications and the automation of HR processes. From the results, the methodology for determining the severity of competences, indicators of behavior are proposed, the strengths and weaknesses of the company’s staff management system in the COVID-19 conditions are taken into account. The practical usability of work is due to the proposed competency-based approach, which makes it possible to increase the efficiency of personnel selection, taking into account key macro-competencies that find an applied form through appropriate behavioral indicators.

This work is interested to optimize the job shop scheduling problem with a no wait constraint. This constraint occurs when two consecutive operations in a job must be processed without any waiting time either on or between machines. The no wait job shop scheduling problem is a combinatorial optimization problem. Therefore, the study presented here is focused on solving this problem by proposing strategy for making Jaya algorithm applicable for handling optimization of this type of problems and to find processing sequence that minimizes the makespan (Cmax). Several benchmarks are used to analyze the performance of this algorithm compared to the best-known solutions.

Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.

The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed.

We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials.

Letters to the Editor-in-Chief are highly encouraged.