Management and Production Engineering Review

In this article we present an industrial application of our mathematical model that integrates

planning and scheduling. Our main objective is to concretize our model and compare the

reel results with the theoretical ones. Our application is realized on a conditioning line of

pharmaceutical products at the ECAM EPMI production laboratory. For this reason and to

save time, we used Witness simulation tool. It gives an overall idea of how the line works,

the Makespan of each simulation and it highlights areas for improvement. We looked for

the best resulting sequence which corresponds to the minest Makespan and total production

cost. Then this sequence is applied on the conditioning line of pharmaceutical products for

simulation. On the other hand, we program our mathematical model with the parameters of

the conditioning line under python in version 3.6 and we adopt a simulation/optimization

coupling approach to verify our model.

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.

Maintenance of process plants requires application of good maintenance practice due to

a great level of complexity. From a plant maintenance point of view, the most significant activity

is turnaround, an activity carried out through project task with long planning process

period and very short execution period, which makes it one of the most complex projects

of maintenance in general. It is exactly this kind of maintenance that is based on multidisciplinarity

which has to be implemented through the system of quality management on all

levels of maintenance management. This paper defines the most significant factors determining

the process of turnaround projects quality management and its efficiency. Such relation

is observed through moderating influence of complexity on process management efficiency

in the turnaround project. The empirical research was conducted based on the survey of

turnaround project participants in five refineries in Croatia, Italy, Slovakia and Hungary.

For exploring the influence of research variables testing of the target relation is carried out

by applying logistical regression. Research results confirm the significance of complexity as

variable that significantly contributes to the project performance through the moderating

influence on success of the project, as well as the influence of an efficient management on

a plant turnaround project key results. Beside theoretical indications, practical implications

that arise from this research study mainly refers to management process of the industrial

plant maintenance project.

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.

The Industry 4.0 Concept assumes that the majority of industry’s resources will be able

to self-diagnose; this will, therefore, enable predictive maintenance. Numerically controlled

machines and devices involved in technological processes should, especially, have the facility

to predict breakdown. In the paper, the concept of a predictive maintenance system for

a vacuum furnace is presented. The predictive maintenance system is based on analysis of the

operating parameters of the system and on the algorithms for identifying emergency states in

the furnace. The algorithms will be implemented in the monitoring sub-system of the furnace.

Analysis of the operating parameters of vacuum furnaces, recorded in the Cloud will lead to

increased reliability and reduced service costs. In the paper, the research methodology for

identification of the critical parameters of the predictive maintenance system is proposed.

Illustrated examples of the thermographic investigation of a vacuum furnace are given.

The article deals with the subject of recruitment of a candidate for a creative team in manufacturing

company. For this purpose, a recruitment model has been developed. It consists

of three main stages: preliminary selection of candidates, assessment of the predispositions

of the selected candidates to work in a team and creative team building. The authors developed

recruitment model of a candidate for a creative team includes a set of tools supporting

the assessment at each stage. In the first stage concerning the preliminary selection, a competence

Questionnaire for working in a creative team, was developed. The second stage

includes the assessment of a candidate’s predispositions with the use of original tools for

assessing creativity, a tool supporting the monitoring of employees’ activity in proposing

innovative solutions and assessment center methodology. The principles of AC remained the

same. The competences that a creative team should possess were adjusted to the tool. Tasks

were proposed in order to assess these competences. The tool itself is ready for application.

In the subsequent stage of research, the tool in question will be tested in selected companies

and evaluated. The last stage concerns the team building. The tool used at this stage is

the Questionnaire for assessing the role in the team. While creating a recruitment model of

a candidate for a creative team, of the selected companies team leaders were consulted.

In the assembly industry, almost all components are outsourced or transferred to other

parties, in order to meet the need for supply. This is referred as outsourcing of production.

The outsourcing of assembly product components is based on a relationship model

between the contractor and the industry. However, there is no relationship or communication

pattern between the contractor or supplier and the assembler. Hence, in order to

accelerate line production and overcome problems with assembly components, the communication

path is shortened by providing a direct communication channel between the

assembler and the supplier or contractor, in order to communicate any problems that arise

during the assembly process by internal communication within the industry. The purpose

of this study is the design and development of a web-based software application electronic

data interchange (EDI) that can be used as a tool for communication between the assembler

and supplier. The EDI application provides formal communication between the assembly

industry and the contractor providing the components or parts needed in the assembly process.

The main purpose of using EDI technology is to help the assembler to communicate

the relevant documents to suppliers quickly, accurately and efficiently. The documents to

be communicated are in the form of reports or claims, and are related to non-conformities,

errors and component difficulties arising during the assembly process. This research novelty

is providing direct communication between assembly and supplier by using EDI application

that can give contribution in manufacturing area so it can accelerate the line production in

assembly.

In the two-sided mixed-model assembly line, there is a process of installing two single stations

in each position left and right of the assembly line with the combining of the product model.

The main aim of this paper is to develop a new mathematical model for the mixed model

two-sided assembly line balancing (MTALB) generally occurs in plants producing large-sized

high-volume products such as buses or trucks.

According to the literature review, authors focus on research gap that indicate in MTALB

problem, minimize the length of the line play crucial role in industry space optimization.In

this paper, the proposed mathematical model is applied to solve benchmark problems of

two-sided mixed-model assembly line balancing problem to maximize the workload on each

workstation which tends to increase the compactness in the beginning workstations which

also helps to minimize the length of the line.

Since the problem is well known as np-hard problem benchmark problem is solved using

a branch and bound algorithm on lingo 17.0 solver and based on the computational results,

station line effectiveness and efficiency that is obtained by reducing the length of the line in

mated stations of the assembly line is increased.

In the existent world of continuous production systems, strong attention has been waged

to anonymous risk that probably generates significant apprehension. The forecast for net

present value is extremely important for any production plant. The objective of this paper

is to implement Monte Carlo simulation technique for perceiving the impact of risk and uncertainty

in prediction and forecasting company’s profitability. The production unit under

study is interested to make the initial investment by installing an additional spray dryer

plant. The expressive values acquied from the Monte Carlo technique established a range of

certain results. The expected net present value of the cash flow is $14,605, hence the frequency

chart outcomes confirmed that there is the highest level of certainty that the company

will achieve its target. To forecast the net present value for the next period, the results

confirmed that there are 50.73% chances of achieving the outcomes. Considering the minimum

and maximum values at 80% certainty level, it was observed that 80% chances exist

that expected outcomes will be between $5,830 and $22,587. The model’s sensitivity results

validated that cash inflows had a greater sensitivity level of 21.1% and the cash inflows for

the next year as 19.7%. Cumulative frequency distribution confirmed that the probability

to achieve a maximum value of $23,520 is 90 % and for the value of $6,244 it is about 10 %.

These validations suggested that controlling the expenditures, the company’s outflows can

also be controlled definitely.

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.

The paper presents an example of Instance-Based Learning using a supervised classification

method of predicting selected ductile cast iron castings defects. The test used the algorithm

of k-nearest neighbours, which was implemented in the authors’ computer application. To

ensure its proper work it is necessary to have historical data of casting parameter values

registered during casting processes in a foundry (mould sand, pouring process, chemical

composition) as well as the percentage share of defective castings (unrepairable casting defects).

The result of an algorithm is a report with five most possible scenarios in terms of

occurrence of a cast iron casting defects and their quantity and occurrence percentage in

the casts series. During the algorithm testing, weights were adjusted for independent variables

involved in the dependent variables learning process. The algorithms used to process

numerous data sets should be characterized by high efficiency, which should be a priority

when designing applications to be implemented in industry. As it turns out in the presented

mathematical instance-based learning, the best quality of fit occurs for specific values of

accepted weights (set #5) for number k = 5 nearest neighbours and taking into account the

search criterion according to “product index”.

Current fast development requires continuous improvement of employees’ skills and knowledge.

Therefore, companies are looking for the best way for improving the employees’ qualifications

and understanding of new concepts and tools which have to be implemented in

manufacturing areas. One method employs gamification for this purpose. The aim of this

paper is to present how gamification can increase the acquisition of knowledge concerning

lean manufacturing concept implementation. Gamification is an active learning approach for

people who will understand the subject easier by ‘feeling’ and ‘touching’ personally the analysed

problems. The research utilized a questionnaire which assessed the game participants’

engagement level. The assessment focused specifically on the participants’ motivation, cognitive

processing and social aspects. The participants were also examined before and after the

game in order to assess the increase of their understanding of different lean manufacturing

topics and tools. Five different games with different groups of participants were played. The

results confirmed the hypothesis that gamification has a positive impact on the knowledge

acquisition as well as on motivation, cognitive processing and social aspects. Finally, various

insights on how to better design, conduct and utilize gamification in the similar technical

context are presented.

Time-of-use (TOU) electricity pricing has been applied in many countries around the world

to encourage manufacturers to reduce their electricity consumption from peak periods to

off-peak periods. This paper investigates a new model of Optimizing Electricity costs during

Integrated Scheduling of Jobs and Stochastic Preventive Maintenance under time of-use

(TOU) electricity pricing scheme in unrelated parallel machine, in which the electricity price

varies throughout a day. The problem lies in assigning a group of jobs, the flexible intervals

of preventive maintenance to a set of unrelated parallel machines and then scheduling of jobs

and flexible preventive maintenance on each separate machine so as to minimize the total

electricity cost. We build an improved continuous-time mixed-integer linear programming

(MILP) model for the problem. To the best of our knowledge, no papers considering both

production scheduling and Stochastic Preventive Maintenance under time of-use (TOU) electricity

pricing scheme with minimization total Electricity costs in unrelated parallel machine.

To evaluate the performance of this model, computational experiments are presented, and

numerical results are given using the software CPLEX and MATLAB with then discussed.

Results of scientific researches show the trend of active using nitrides and borides of transition

metals and their combination in developing protective materials. While single elements

nitrides have been well studied, their multilayer modifications and combinations require

more detailed study. Physical-mechanical properties and structural-phase state of multilayer

coating according to the deposition conditions is an important task for the study.

It will be the analysis of physical-mechanical and electrical properties of coatings based on

refractory metals nitrides, their structure and phase composition and surface morphology

depending on the parameters of condensation. It was established the structure and behavior

of nano scale coatings based on refractory metals nitrides (Ti, Zr) depending on the size

of nano grains, texture, stress occurring in coatings.