The article includes presentation of fuzzy numbers application in projects prioritizing at

manufacturing and service providing enterprises. The following criteria have been applied

as a basis for projects prioritizing analysis in enterprise: NPV index, linked with the enterprise strategic aims, project execution cost, project time, project scope and risk. As the

criteria selected were of measurable and non-measurable character in projects prioritizing

evaluation, the fuzzy decision making system has been developed, in which a linguistic value

has been defined for each criterion of projects prioritizing. Knowledge base has been developed afterwards, presenting cause-effect dependencies in projects prioritizing. Knowledge

base consisted of conditional rules. Fuzzy system of decision making in project prioritizing

has been developed in MATLAB application.

The decision making fuzzy system established, constitutes an efficient tool for projects prioritizing, on the basis of criteria given and concluding system developed. The obtained analysis

results provide basis for the decision making parties to set the projects execution sequences.

Make-To-Stock (MTS) and Make-To-Order (MTO) are the two traditional strategies in

production management. In the case of the MTS there is a growing demand for a new

approach, which is called Make-To-Availability (MTA) strategy. The paper characterizes and

compares the MTS and MTA strategies. The comparative analysis based, among others, on

computational experiments carried out in a computer program developed in Microsoft Visual

Studio 2017 Environment was presented. The models have been prepared for both strategies

with the same assumptions: external conditions (market demand) and internal conditions

(structure of the production process). The investigation of how the strategies respond to

various scenarios of demand intensity was done. The simulation models were prepared and

validated for the case of the production line in one of the industrial automation company.

The research shows that the use of the MTA strategy in the majority of cases gives much

better results than the use of the MTS strategy due to the minimization of storage costs and

the costs of non-fulfillment of the customers’ demand. The directions for further research

were also presented.

This paper focuses on the analysis of selected risks as part of investments in the power

engineering at the initial (tender) stage of the life cycle in the context of the method of

project management by the Contractor. The study was carried out on the basis of an

analysis of over 500 tenders in the power engineering, from the last 5 years, taking into

account future forecast data. The analysis carried out in this article was aimed at achieving

specific and unique goals and results aimed at creating a useful product, which is the

Contractor’s offer in the power engineering, taking into account the most significant risks.

The result of this article is to support the project team in implementing risk management

in the project at the tender stage. For this purpose, the risks with their basic parameters

were defined, which allowed for the development of a risk matrix taking into account the

data obtained in the tender procedures of leading electric power distributors. Based on

the proposed risk quantification criteria, a list of remedial actions was prepared for all risk

types listed in this article. In addition, the aspects of possible elimination/reduction of the

impact of the most significant risks that occur at the analyzed stage of the investment life

cycle were developed.

The industry transformation to the digital model 4.0 will be a significant change from

the perspective of the organisation and processes. In the context of the above, the research

was undertaken, the principal aim of which constituted the attempt to answer the question

concerning the technological advancement level of manufacturing companies operating in

the agricultural machinery sector. It is about identifying what adaptation projects in the

context of the fourth generation industry era should be undertaken by the Polish manufacturers operating in the agricultural machinery sector. The achievement of the main

objective required formulation and implementation of partial objectives, which, according

to the authors, include: C(1) – defining the Industry 4.0 axiom merit; C(2) – using the

subject literature reconstruction and interpretation methods – nomination of areas, on the

one hand essential from the perspective of the model 4.0, and on the other hand those that

may demonstrate the maturity in the domain of the adopted desiderata; C(3) – compilation

of the research model, in the form of an assessment sheet, being a resultant of literature

studies and research conducted among deliberately selected domain experts; C(4) – based

on the selected indicators, the technological advancement level recognition of the studied

companies; specification of a technological gap (questioning among experts).

Industrial engineers gather knowledge during their bachelor studies through lectures and

practical classes. The goal of practical class might be an extension of knowledge and/or a

consolidation and application of already gathered knowledge. It is observed that there exists

a gap between theory learnt during lectures and practical classes. If practical classes require

holistic approach and solving complex tasks (problems), students strive with understanding

relations and connections between parts of knowledge. The aim of this article is to show an

example of a simple practical assignment that can serve as a bridge between lectures and

practical classes through discussion of interactions and relations between parts of theoretical

knowledge. It is an example of in-class simulating of a line and cellular layout considering

discussion of elements impacting and impacted by the type of layout (e.g. learning curve,

changeovers, etc.). In-class verification of the presented approach confirmed its usability for

teaching industrial engineers and bridging the gap between theory delivered through lectures

and more advanced practical classes.

The focus of this paper is to propose a method for prioritizing knowledge and technology

factor in companies’ business strategy. The data has been gathered and analyzed from

Malaysian-owned company of medium size type industry, employing around 250 employees

and listed in the Malaysian Bourse Stock of Exchange, since 2000. Sense and respond model

is used to determine competitive priorities of the firms. Then knowledge and technology

part of sense and respond questionnaire is used to calculate the variability coefficient i.e. the

uncertainty caused by technology and knowledge factor. The results show that the company

is not leading in term of technology (spear head technology share is around 33%). Therefore,

the enhancement of technology and knowledge to SCA values is not significantly seen in

this study. The usage of the core technologies is around 41% and it might seem relatively

enough. In terms of basic technology, while its share is the lowest (around 25%), it has the

highest source of uncertainties among technology types. In this case, the proposed model

helped to have a clear and precise improvement plan towards prioritizing technology and

knowledge focus.

The objective of this research is to investigate the perception of owner – managers and

their employees regarding entrepreneurial leadership. To develop the research, two questions

are raised related to the similarities or differences of the perceptions of both groups

with what is established in the literature and between the self – evaluation of the owner –

managers and their employees on whether the former perform as an entrepreneurial leader.

As a research method, both groups are asked to perform, first individual evaluations and

then to match certain behaviours and the levels at which they should appear at certain levels

of entrepreneurial leadership capacity. The data gathered during the investigation were

processed using the Categorical Principal Components Analysis and revealed the similarities

and differences between the perceptions of the owner-managers and their employees on

entrepreneurial leadership. In spite of not finding significant differences between what is established

in the literature and among the perceptions of the groups under study, interesting

nuances stand out that, if not identified and understood, could have a negative effect on

the performance of SMEs. The results of the research demonstrated the importance of the

approach of behaviour and perception in the study of entrepreneurial leadership.

This paper explores selected heuristics methods, namely CDS, Palmer’s slope index, Gupta’s

algorithm, and concurrent heuristic algorithm for minimizing the makespan in permutation

flow shop scheduling problem. Its main scope is to explore how different instances sizes

impact on performance variability. The computational experiment includes 12 of available

benchmark data sets of 10 problems proposed by Taillard. The results are computed and

presented in the form of relative percentage deviation, while outputs of the NEH algorithm

were used as reference solutions for comparison purposes. Finally, pertinent findings are

commented.

The objective of the milk-run design problem considered in this paper is to minimize transportation

and inventory costs by manipulating fleet size and the capacity of vehicles and

storage areas. Just as in the case of an inventory routing problem, the goal is to find a periodic

distribution policy with a plan on whom to serve, and how much to deliver by what

fleet of tugger trains travelling regularly on which routes. This problem boils down to determining

the trade-off between fleet size and storage capacity, i.e. the size of replenishment

batches that can minimize fleet size and storage capacity. A solution obtained in the declarative

model of the milk-run system under discussion allows to determine the routes for each

tugger train and the associated delivery times. In this context, the main contribution of

the present study is the identification of the relationship between takt time and the size

of replenishment batches, which allows to determine the delivery time windows for milkrun

delivery and, ultimately, the positioning of trade-off points. The results show that this

relationship is non-linear.

Redundancy based methods are proactive scheduling methods for solving the Project

Scheduling Problem (PSP) with non-deterministic activities duration. The fundamental

strategy of these methods is to estimate the activities duration by adding extra time to the

original duration. The extra time allows to consider the risks that may affect the activities

durations and to reduce the number of adjustments to the baseline generated for the project.

In this article, four methods based on redundancies were proposed and compared from two

robustness indicators. These indicators were calculated after running a simulation process.

On the other hand, linear programming was applied as the solution technique to generate

the baselines of 480 projects analyzed. Finally, the results obtained allowed to identify the

most adequate method to solve the PSP with probabilistic activity duration and generate

robust baselines.

The objectives of this study were to develop a framework of the collaboration network, operational

performance, and reverse logistics determinants on the performance outcomes of the

auto parts industry, and to study the direct, indirect, and overall effects of the factors that

influence the performance outcomes of the auto parts industry. This quantitative research

utilized a questionnaire as the tool for data collection, which was completed by the managers

in the auto parts industry from 320 companies. According to the analysis with the Structural

Equation Modeling (SEM), it was found that the collaboration networks, operational

performance, and reverse logistics positively affect the performance outcomes; whereas, the

collaboration networks mainly affect the development of organizations by causing performance

outcomes to continue growing unceasingly, including the enhancement of sustainable

competitive capacity and the operational results of the auto parts industry.

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.

Rescheduling is a frequently used reactive strategy in order to limit the effects of disruptions

on throughput times in multi-stage production processes. However, organizational deficits

often cause delays in the information on disruptions, so rescheduling cannot limit disruption

effects on throughput times optimally. Our approach strives for an investigation of

possible performance improvements in multi-stage production processes enabled by realtime

rescheduling in the event of disruptions. We developed a methodology whereby we

could measure these possible performance improvements. For this purpose, we created and

implemented a simulation model of a multi-stage production process. We defined system

parameters and varied factors according to our experiment design, such as information delay,

lot sizes and disruption durations. The simulation results were plotted and evaluated

using DoE methodology. Dependent on the factor settings, we were able to prove large improvements

by real-time rescheduling regarding the absorption of disruption effects in our

experiments.

The article presents tools, methods and systems used in mechanical engineering that in

combination with information technologies create the grounds of Industry 4.0. The authors

emphasize that mechanical engineering has always been the foundation of industrial activity,

while information technology, the essential part of Industry 4.0, is its main source of innovation.

The article discusses issues concerning product design, machining tools, machine tools

and measurement systems.

At present, the speed of production and its complexity increases with each passing year due

to the shorter product life cycle and competition in the global market. This trend is also

observed in the machine-building industry, therefore, in order to ensure the competitiveness

of enterprises and reduce the cost of production, it is necessary to intensify production.

This is especially true in the machining of complex parts that require a great number of

setups, and technological equipment. The problem-oriented analysis of complex parts was

carried out, the parts classification was structured and developed according to the design

and technological features. This made it possible to offer advanced manufacturing processes

for complex parts like levers, forks, and connecting rods. The flexible fixtures for specified

complex parts were developed. The effectiveness of the proposed manufacturing processes,

Fault Tree is one of the traditional and conventional approaches used in fault diagnosis. By

identifying combinations of faults in a logical framework it’s possible to define the structure

of the fault tree. The same go with Bayesian networks, but the difference of these probabilistic

tools is in their ability to reasoning under uncertainty. Some typical constraints to the

fault diagnosis have been eliminated by the conversion to a Bayesian network. This paper

shows that information processing has become simple and easy through the use of Bayesian

networks. The study presented showed that updating knowledge and exploiting new knowledge

does not complicate calculations. The contribution is the structural approach of faults

diagnosis of turbo compressor qualitatively and quantitatively, the most likely faults are

defined in descending order. The approach presented in this paper has been successfully

applied to turbo compressor, which represent vital equipment in petrochemical plant.

Industry 4.0 will affect the complexity of supply chain networks. It will be necessary to

adapt more and more to the customer and respond within a time interval that is willing

to accept the product waiting. From these considerations, there is a need for a different way

of managing the supply chain. The traditional concept of supply chain as a linear system,

which allows optimizing individual subsystems, thus obtaining an optimized supply chain, is

not enough. The article deals with the issue of supply chain management reflecting demand

behaviour using the methodology Demand Driven MRP system. The aim of the publication

is to extend the knowledge base in the area of demand-driven supply logistics in the

The supply chain of spare parts is the intersection between the supply chain, the after-sales

and the maintenance services. Some authors have tried to define improvement paths in terms

of models to satisfy the performance criteria. In addition, other authors are directed towards

the integration of risk management in the demand forecasting and the stock management

(performance evaluation) through probabilistic models. Among these models, the probabilistic

graphical models are the most used, for example, Bayesian networks and petri nets.

Performance evaluation is done through performance indicators.

To measure the appreciation of the supply of the spare parts stock, this paper focuses on the

performance evaluation of the system by petri nets. This evaluation will be done through

an analytical study. The purpose of this study is to evaluate and analyze the performance of

the system by proposed indicators. First, we present a literature review on Petri nets which

is the essential tool in our modeling. Secondly, we present in the third section the analytical

study of the model based on bath deterministic and stochastic petri networks. Finally, we

present an analysis of the proposed model compared to the existing ones.

The field of academic research on corporate sustainability management has gained significant

sophistication since the economic growth has been associated with innovation. In this paper,

we are to show our research project that aims to build an artificial intelligence-based neurofuzzy

inference system to be able to approximate company’s innovation performance, thus

the sustainability innovation potential. For this we used an empirical sample of Hungarian

processing industry’s large companies and built an adaptive neuro fuzzy inference system.

The article presents the issue related with a proper preparation of a data sheet for the

analysis, the way of verifying the correctness and reliability of input information, and proper

data encoding. Improper input or coding of data can significantly influence the correctness

of performed analyses or extend their time. This stage of an analysis is presented by an

authorship questionnaire for the study on occupational safety culture in a manufacturing

plant, using the Statistica software for analyses. There were used real data, obtained during

the research on the issue of occupational safety and factors having the greatest influence on

the state of occupational safety.

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 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.

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.

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.