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1

Analysis of Production Process Performance Using Computer

Pawlak Szymon, Fornalczyk Agnieszka

Management Systems in Production Engineering

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2025

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nr 3 (33)

414--419

EN

Planning a production process in terms of correctly defining its efficiency, duration and the level of generated costs is a difficult task. Manufacturing processes are characterized by a high level of complexity and are exposed to a large number of external factors that are difficult to predict. In many cases, one of the tools supporting decisions in the analysis of manufacturing process parameters is the use of computer simulation both at the process planning stage and in real time during its implementation. In this article, a computer simulation tool (FlexSim simulation software) was used to analyze the parameters of a selected production process. The conducted analyses allowed for indicating the direction of actions in the use of computer simulation as a decision support tool at selected stages of production process planning in the area of evaluating solutions aimed at implementing improvements.

2

Optimizing resource management under variable geological and mining conditions using a longwall advance model

Galica Dominik, Kopacz Michał, Chmura Damian, Kulpa Jarosław, Kaczmarzewski Sylwester, Malinowski Leszek, Sobczyk Eugeniusz Jacek, Jarosz Jacek, Dyczko Artur, Olczak Piotr, Kicki Jerzy, Toś Piotr

Gospodarka Surowcami Mineralnymi

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2025

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Vol. 41, iss. 4

73--100

EN

Production planning in underground hard coal mines faces high uncertainty from geological variability. The longwall face advance is a key parameter determining production outcomes. This article models this advance rate based on local geological, hazard, technical, and organizational parameters. Instead of tonnage (a composite parameter), this research models the linear advance rate itself, representing the primary and most unpredictable component of excavation. This provides a utilitarian tool for decision-support systems and efficient deposit management. The research used integrated 5-year data from three hard coal mines, acquired from digital deposit models, scheduling systems, and operational reports, and aggregated monthly. Following a selection from 71 variables, a final set of 26 independent variables and one dependent variable (longwall advance per shift with production) was chosen. Linear Mixed Models (LMMs) were applied to incorporate the hierarchical data structure (seams nested within mines). The model demonstrates a good fit, explaining 64% of total variance (conditional R2c = 0.64), while fixed effects alone account for 43% (marginal R2m = 0.43). Results indicate organizational factors have a dominant impact. The random effects analysis revealed 33.2% of residual variance stems from immeasurable, systematic differences between mines, highlighting the crucial role of mine-specific management factors. By successfully quantifying these diverse factors within a stable LMM, this study provides a model with improved predictive accuracy, establishing an effective foundation for operational planning and resource management.

PL

Planowanie produkcji w kopalniach węgla kamiennego obarczone jest dużą niepewnością wynikającą ze zmienności geologiczno-górniczej. Postęp ściany jest kluczowym parametrem determinującym wyniki produkcyjne. W artykule modelowano tempo postępu ściany w funkcji lokalnych uwarunkowań geologicznych, zagrożeń oraz parametrów technicznych i organizacyjnych. Badania koncentrują się na modelowaniu postępu liniowego (podstawowego i najbardziej nieprzewidywalnego komponentu eksploatacji) zamiast tonażu (parametru złożonego). Dostarcza to narzędzia dla systemów wspomagania decyzji i efektywnej gospodarki złożem. Badania oparto na zintegrowanych, 5-letnich danych z trzech kopalń węgla kamiennego. Dane pozyskano z cyfrowych modeli złóż, systemów harmonogramowania i raportów operacyjnych, agregując je miesięcznie. Po selekcji z 71 zmiennych wybrano 26 predyktorów i 1 zmienną zależną (postęp ściany na zmianę produkcyjną). Zastosowano Liniowe Modele Mieszane (LMM) w celu uwzględnienia hierarchicznej struktury danych (pokłady w kopalniach). Opracowany model wykazuje dobre dopasowanie, wyjaśniając 64% całkowitej wariancji (warunkowe R2c = 0.64), przy czym efekty stałe odpowiadają za 43% (marginalne R2m = 0.43). Wyniki wskazują na dominujący wpływ czynników organizacyjnych. Analiza efektów losowych ujawniła, że 33.2% wariancji resztowej wynika z niemierzalnych, systematycznych różnic między kopalniami, co podkreśla kluczową rolę czynników zarządczych. Rezultatem niniejszej pracy jest stabilny model LMM, który poprzez integrację i kwantyfikację czynników geologicznych, operacyjnych oraz organizacyjnych (włącznie z efektami losowymi) oferuje zwiększoną zdolność prognostyczną. Model ten tworzy tym samym efektywną podstawę dla planowania operacyjnego i gospodarki zasobami.

3

Method for estimating the size of mineable resource base in the concept of an effective exploitation parcel (EPE)

Malinowski Leszek, Kopacz Michał, Sobczyk Jacek, Kulpa Jarosław, Galica Dominik, Olczak Piotr, Jarosz Jacek, Dyczko Artur, Kaczmarzewski Sylwester, Kicki Jerzy

Gospodarka Surowcami Mineralnymi

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2025

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Vol. 41, iss. 3

167--195

EN

The paper presents an authorial method of determining the deposit resource base considering changing market conditions. To achieve this goal authors built the dedicated software, which optimizes mining schedules taking into account the expected impact of geological and mining factors and natural hazards on the exploitation process. The research method developed, and the IT tool built, enables the analysis of thousands of variants of cutting the mining plots in order to identify ones that maximize the profit potential of longwalls and parcels. In this method the potential is measured by the value of the operating margin and profit, which include capital expenditure and operating costs of coal production. The impact of geological, mining and natural hazard factors is identified in a multicriteria method. Then, by estimating the authorial risk index RI, the cost of equity – the weighted component of the mining company’s cost of capital – is adjusted. The results of the presented example show that even small changes in raw material price may significantly affect the amount of recoverable resources and the economic value of the project (NPV). Resource base in the analyzed cases ranges from 0 to 45 million Mg and the NPV from 0 to 7.8 billion PLN. For the base price scenario effective resources amount to 19.4 million Mg, which represents only 42% of the proven recoverable resources. The approach used is in line with the requirements of the JORC Code and enables multivariate analysis of tunnel layouts using advanced digital tools.

PL

W artykule zaprezentowano autorską metodę określania wielkości bazy zasobowej złoża w zależności od zmiennych warunków rynkowych. Do realizacji tego celu zastosowano dedykowane oprogramowanie do optymalizacji harmonogramów produkcji górniczej z uwzględnieniem oczekiwanego wpływu czynników geologicznych, górniczych i zagrożeń na wydobycie węgla kamiennego. Opracowana metoda badawcza i zbudowane narzędzie informatyczne umożliwiają analizę tysięcy wariantów rozcinki złoża i parcel eksploatacyjnych celem identyfikacji wariantów zagospodarowania maksymalizujących potencjał dochodowy ścian i parcel. W niniejszej metodzie etapie potencjał ten jest mierzony wartością marży operacyjnej i zysku szacowanego po uwzględnieniu nakładów inwestycyjnych i kosztów operacyjnych produkcji węgla. Wpływ czynników geologicznych, górniczych i zagrożeń naturalnych jest identyfikowany w metodzie wielokryterialnej, a następnie poprzez szacowanie autorskiego indeksu ryzyka RI korygowany jest koszt kapitałów własnych - składnik ważonego kosztu kapitału przedsiębiorstwa górniczego. Wyniki przykładu obliczeniowego wskazują, że nawet niewielkie zmiany cen surowca mogą znacząco wpływać na opłacalność eksploatacji, skalę zasobów możliwych do pozyskania oraz wartość ekonomiczną projektu (NPV), przy czym w analizowanym przypadku baza zasobowa wahała się od 0 do 45 mln Mg, a N PV od 0 do 7,8 mld PLN. Dla scenariusza bazowego oszacowana wielkość zasobów efektywnych ekonomicznie sięgnęła 19,4 mln Mg, co stanowi zaledwie 42% zasobów udokumentowanych w kategorii zasobów operatywnych (wydobywalnych). Zastosowane podejście wpisuje się w wymagania systemu klasyfikacji zasobów JORC Code i umożliwia wielowariantową analizę geometrii wyrobisk z wykorzystaniem zaawansowanych narzędzi cyfrowych.

4

Analytical Research on Operational Issues of the Remanufacturing Process in India

Sinha Ajay Kumar, Rao Hanumantha

Management and Production Engineering Review

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2023

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Vol. 14, No. 4

19--27

EN

Environmental awareness among the masses compelled many companies to adopt sustainable practices in their business operations. Remanufacturing is a well-tested and successful business model practiced in many European countries. But in many African and Asian countries, it is still nascent, including India. This research study tries to identify the critical factors in the “Operational Management” area for the viability of remanufacturing business in India. For this purpose, a questionnaire was developed based on the important factors identified from the extensive literature review. An online questionnaire survey was conducted among Indian white goods appliance manufacturing companies and their suppliers. The responses were analyzed statistically and ranked based on their criticality in initiating remanufacturing business in India. The findings may help the Indian government and manufacturing firms to frame proper strategies related to the operational management issues of remanufacturing business in India.

5

The geological modelling of deposits, production designing and scheduling in the JSW SA Mining Group

Dyczko Artur

Gospodarka Surowcami Mineralnymi

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2023

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T. 39, z. 1

35--62

EN

The paper presents the analysis of IT tools selection to develop a system of deposits geological modelling as well as production designing and scheduling in a hard coal mine. The presented concept creates a subject-matter foundation of the solution supporting the decision making system in the field of production activities performance, with the use of IT solutions and monitoring of end product quality, implemented under the paradigm of so-called Intelligent Mine. A technological dialogue carried out by questionnaire surveys, supported with experts’ opinions, was applied to select the software for designing a system of deposit modelling, and for designing and scheduling of mining operations. Questionnaires originated based on presentations, covering the functionality in the field of geological data gathering, developing a geological spatial model of a bedded deposit, as well as designing and scheduling. The presented solutions were next evaluated, via questionnaires, by the employees of the company. In addition, 4 groups of criteria were prepared: technical (questionnaires), technical (experts), business, and IT, based on which the final evaluation was carried out. Ultimately, Solution 2 was selected as that, which to the highest degree satisfied technical, business, and IT requirements of the planned system. The indicated IT solution was implemented and became one of basic tools for modelling hard coal deposits, an also for designing and scheduling of the mining operations in the company.

PL

Rozwój informatyki, automatyki i robotyki umożliwia coraz większej liczbie podmiotów zwiększenie wykorzystania technik cyfrowych lub komputerowych. Dotyczy to również branży tradycyjnych, takich jak górnictwo, dla których stosowanie narzędzi informatycznych do gromadzenia, przechowywania i przetwarzania danych również powinno być jednym z priorytetów. Grupa Kapitałowa JSW SA, zajmująca się wydobyciem węgla kamiennego oraz produkcją koksu, przeprowadziła badania w zakresie opracowania i wdrożenia systemu do modelowania złoża oraz harmonogramowania produkcji górniczej. Celem stosowania wdrożonego systemu była realizacja nadrzędnego celu Programu Jakość Grupy Kapitałowej, czyli zwiększenia efektywności zarządzania jakością złoża i produktu handlowego. W artykule przedstawiono jeden z etapów badań, którym był wybór dedykowanych narzędzi informatycznych dla potrzeb modelowania geologicznego złóż oraz projektowania i harmonogramowania produkcji. Opracowane rozwiązanie pozwala na stałą aktualizację informacji w bazie danych, szybkie ich wykorzystanie i modyfikację oraz usprawnienie procesu projektowego (roboty udostępniające, przygotowawcze, jak i eksploatacyjne). System pozwala na planowanie (krótko- i długoterminowe) eksploatacji oraz projektowanie techniczne, projektowanie robót udostępniających, przygotowawczych i eksploatacyjnych oraz wykonanie harmonogramu projektowanych robót. Umożliwia automatyczne obliczanie ilości i jakości urobku oraz skały płonnej w wybranych przedziałach czasowych oraz przygotowanie prognozy dla wszystkich parametrów dotyczących wykonanego projektu wydobycia, takich jak: ilość urobku, ilość skały płonnej, parametry jakościowe itp.

6

Efficient exact A* algorithm for the single plant Hydro Unit Commitment problem

Heintzmann Alexandre, Artigues Christian, Bendotti Pascale, Ngueveu Sandra Ulrich, Rottner Cécile

Annals of Computer Science and Information Systems

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2023

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Vol. 35

533--543

EN

The Hydro Unit Commitment problem (HUC) specific to hydroelectric plants is part of the electricity production planning problem, called Unit Commitment Problem (UCP). More specifically, the studied case is that of the HUC with a single plant, denoted 1-HUC. The plant is located between two reservoirs. The horizon is discretized in time periods. The plant operates at a finite number of points defined as pairs of the generated power and the corresponding water flow. Several constraints are considered. Each reservoir has an initial volume, as well as window resource constraints, defined by a minimum and maximum volume per time period. At each time period, there is an additional positive, negative or zero intake of water in the reservoirs. The case of a price-taker revenue maximization problem is considered. An efficient exact A* variant, so called HA*, is proposed to solve the 1-HUC accounting for window constraints, with a reduced search space and a dedicated optimistic heuristic. This variant is compared to a classical Resource Constrained Shortest Path Problem (RCSPP) algorithm and a Mixed Integer Linear Programming formulation solved with CPLEX. Results show that the proposed algorithm outperforms both concurrent alternatives in terms of computational time in average on a set of realistic instances, meaning that HA* exhibits a more stable behavior with a larger number of instances solved.

7

Using Internet of Services to Stablish a Service-Oriented Manufacturing Architecture model in Industry 4.0

Reis Jacqueline Zonichenn, Goncalves Rodrigo Franco, Silva Marcia Terra

Management and Production Engineering Review

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2022

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Vol. 13, No. 4

137--151

EN

The manufacturing industry has been reshaping its operations using digital technologies for a smart production towards a more customized demand. Nevertheless, the flexibility to attend the production plan changes in real time is still challenging. Although the Internet of Services (IoS) has been addressed as a key element for Industry 4.0, there is still a lack of clarity about the IoS contribution for advanced manufacturing. Through a case study, the paper aims to validate the adherence of a theoretical model named Service-Oriented Manufacturing Architecture (SOMA) in two manufacturing companies that have been already engaged in Industry 4.0. As main results, it was concluded that IoS could suit in one case of Industry 4.0 flexible production process but not in a mass production one. Considering the scarcity of research that exemplifies the IoS contribution, the present paper brings an important assessment on a real manufacturing scenario.

8

The Pandemic-Type Demand Shocks in the Mean-Variance Newsvendor Problem

Bieniek Milena

Management and Production Engineering Review

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2022

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Vol. 13, No. 1

52--61

EN

The paper considers the negative pandemic-type demand shocks in the mean-variance newsvendor problem. It extends the previous results to investigate the case when the actual additive demand may attain negative values due to high prices or considerable, negative demand shocks. The results indicate that the general optimal solution may differ to the solution corresponding exclusively to the non-negative realizations of demand.

9

Scheduling of the Manufacturing Cell Work with the Use of a Genetic Algorithm on the Example of a Flexible Production System

Matuszny Marcin

Management and Production Engineering Review

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2022

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Vol. 13, No. 4

98--106

EN

The article is to present the application of genetic algorithm in production scheduling in a production company. In the research work the assumptions of the methodology were described and the operation of the proposed genetic algorithm was presented in details. Genetic algorithms are useful in complex large scale combinatorial optimisation tasks and in the engineering tasks with numerous limitations in the production engineering. Moreover, they are more reliable than the existing direct search algorithms. The research is focused on the effectivity improvement and on the methodology of scheduling of a manufacturing cell work. The genetic algorithm used in the work appeared to be robust and fast in finding accurate solutions. It was shown by experiment that using this method enables obtaining schedules suitable for a model. It gives a group of solutions that are at least as good as those created by the heuristic rules.

10

Prioritizing and Scheduling of Production Orders in Non-homogenous Production Systems

Skołud Bożena, Szopa Agnieszka, Kalinowski Krzysztof

Management and Production Engineering Review

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2022

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Vol. 13, No. 1

62--75

EN

The aim of the work was to develop a prioritizing and scheduling method to be followed in small and medium-sized companies operating under conditions of non-rhythmic and nonrepeatable production. A system in which make to stock, make to order and engineer to order (MTS, MTO and ETO) tasks are carried out concurrently, referred to as a non-homogenous system, has been considered. Particular types of tasks have different priority indicators. Processes involved in the implementation of these tasks are dependent processes, which compete for access to resources. The work is based on the assumption that the developed procedure should be a universal tool that can be easily used by planners. It should also eliminate the intuitive manner of prioritizing tasks while providing a fast and easy to calculate way of obtaining an answer, i.e. a ready plan or schedule. As orders enter the system on an ongoing basis, the created plan and schedule should enable fast analysis of the result and make it possible to implement subsequent orders appearing in the system. The investigations were based on data from the non-homogenous production system functioning at the Experimental Plant of the Łukasiewicz Research Network – Institute of Ceramics and Building Materials, Refractory Materials Division – ICIMB. The developed procedure includes the following steps: 1 – Initial estimation of resource availability, 2 – MTS tasks planning, 3 – Production system capacity analysis, 4 – ETO tasks planning, 5 – MTO orders planning, 6 – Evaluation of the obtained schedule. The scheduling procedure is supported by KbRS (Knowledge-based Rescheduling System), which has been modified in functional terms for the needs of this work assumption.

11

Extending Value Stream Mapping for Lean Production Planning and Control

van Landeghem Hendrik, Cottyn Johannes

Management and Production Engineering Review

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2022

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Vol. 13, No. 3

75--82

EN

Value Stream Mapping has been a key Lean tool since its publication in 1988, offering a strategic view on the reconfiguration of an organization’s processes to reduce overall lead time. It has since been used in many different domains beyond (car) manufacturing. However, the potential offered by its concise representation of both material flow and its controlling information flow seems to have been largely underused. Most literature reports on VSM in the context of waste detection and local improvements. VSM also supports redesigning the material flow (even on a supply chain level) towards (pure) pull systems. However, it fails to adequately give guidance on how to gradually evolve towards this ultimate ideal state. This paper wants to offer a significant contribution to practitioners on how to use VSM to bridge this gap. Another key challenge that remains largely unpublished is how to adapt the planning systems accordingly at each reconfiguration of the material flow. This paper presents extensions to the basic VSM tool to meet these challenges. It includes a more comprehensive 5-level hierarchy that allows to position most lean flow-related techniques. It also extends the basic “door-to-door” VSM with new symbols to accommodate these techniques into the map. Finally, it introduces a new set of 13 questions to support redesigning not only the material flow, but also the information flow. The resulting richer future state maps better support the gradual evolution towards a leaner future shop floor, as illustrated with an example.

12

Integrated maintenance, inventory and quality engineering decisions for multi-product systems

Salmasnia Ali, Hafezian Rahil, Maleki Mohammad Reza

Engineering Management in Production and Services

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2022

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Vol. 14, no. 4

94-113

EN

It is essential for manufacturers to consider the interrelation among quality, inventory, and maintenance decisions to detect imperfect quality products, keep the production system in good operating condition, and manage quality and inventory costs. Hence, this paper aims to develop an integrated model of inventory planning, quality engineering, and maintenance scheduling in which the expected total cost per time unit is minimised by determining the sample size, sampling interval, control limit coefficient, along with production cycle time. In this regard, an imperfect multi-product manufacturing system is considered, in which the inventory shortage in satisfying the demand for each product type and the idle time during the production cycle are not allowed. It is assumed that the process starts in an in-control condition where most produced units are conforming. However, due to the occurrence of an assignable cause (AC), the process mean moves to an out-of-control condition in which a significant fraction of non-conforming units is produced. The efficiency of the proposed mathematical model is evaluated by a numerical example, and then the sensitivity of the proposed model to important inputs is analysed. Finally, a comparative study based on the Taguchi design approach is given to confirm the capability of the proposed model to achieve remarkable cost savings.

13

Analytic optimization framework for resilient manufacturing production and supply planning in Industry 4.0 context-buffer stock allocation - case study

Laciuga Maria, Sęp Jarosław

Technologia i Automatyzacja Montażu

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2021

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nr 3

42--50

PL

Planowanie montażu zespołów i wynikające z niego planowanie i harmonogramowanie produkcji (PPS) oraz planowanie zakupu surowców są kluczowymi elementami odpowiedzialnymi za dostawy na czas oraz aspekt kosztowy poprzez odpowiednie obciążenie zasobów oraz nośnik zapasów. Systemy klasy Industry 4.0 poszerzają wiedzę i możliwości dla podniesienia wydajności systemu oraz usprawniają podejmowanie decyzji. Środowisko produkcyjne z uwagi na sieć strumieni wartości, mnogość zmiennych, wielopoziomowe struktury materiałowe staje się bardzo złożone co jest dodatkowo wzmacniane przez nacisk na doskonałość operacyjną. Niepewność zapotrzebowań wymaga dodatkowej atencji oraz integracji z łańcuchem dostaw. W pracy zaprezentowano rozbudowane środowisko dla rozwiązań analitycznych wspierających narzędzia planowania montażu, produkcji oraz zakupów. Ryzyko związane z zmiennymi planami klienta oraz zmiennością dostawców jest ograniczane poprzez zarządzanie buforami. Poziom bufora zależy od predykcji na bazie modelu symulacyjnego opartego na mechanizmach uczenia maszynowego z wykorzystaniem sieci neuronowych w celu zagwarantowania dostaw na czas oraz w oczekiwanym koszcie. Aktualne wyzwania i oczekiwania w obszarze inteligencji opartej na danych zostały zaprezentowane. Rezultaty zaproponowanego modelu zostały szczegółowo porównane ze stanem obecnym.

EN

Advanced components assembly planning and related manufacturing production planning and scheduling (PPS) and supply planningare key elements responsible for deliveries and cost aspects as a resources workload and inventory driver. Industry 4.0 systems broaden science for improving system performance and decision making.Industry site environment because of material flow network, interrelated multi-variable, multilevel production becomes very complex what is challenged by a strong focus on operational excellence. Demand uncertainty requires additional attention and integration with Supply Chain. This paper presents an extended framework for analytics solutions in assembly, production and supply planning for manufacturing company. Risk related to violable customers demand is mitigated by buffer management. Buffer levels relay on a prediction from simulation model using computational methods based on machine learning algorithm using Neutral Networks to guarantee on-time deliveries and rational costs. Actual challenges and requirements for new use cases in data-driven intelligence are presented. The proposed models and the actual state will be comparably discussed with results analyses.

14

Stochastic programming model for production planning with stochastic aggregate demand and spreadsheet-based solution heuristics

Saadouli Nasreddine

Operations Research and Decisions

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2021

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Vol. 31, No. 4

117--127

EN

By discretising the stochastic demand, a deterministic nonlinear programming formulation is developed. Then, a hybrid simulation-optimisation heuristic that capitalises on the nature of the problem is designed. The outcome is an evaluation problem that is efficiently solved using a spreadsheet model. The main contribution of the paper is providing production managers with a tractable formulation of the production planning problem in a stochastic environment and an efficient solution scheme. A key benefit of this approach is that it provides quick near-optimal solutions without requiring in-depth knowledge or significant investments in optimisation techniques and software.

15

The Way of ETO SMEs to Mass Customization – Overview from Real Production Systems

Ciesla Bartosz, Mleczko Janusz

Management and Production Engineering Review

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2021

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Vol. 13, No. 3

97--105

EN

In this article conclusions from nearly 10 years of collaboration with Polish and German Engineer-to-Order (ETO) small and medium-sized enterprises (SMEs) from mechanical sector was presented. Research objective was to highlight common organizational problems they are dealing with, which prevent them from transition to Mass Customizers. As a result, a concept of 5 foundations for robust process design was proposed: procedures, product selection, machining philosophy, planning and storage, cross-functional teams. More practical solutions from this field have to be published to fill the research gap.

16

A Method to Improve Planning of Product Placement on a Printing Sheet

Czerniachowska Kateryna, Żywicki Krzysztof, Wichniarek Radosław

Management and Production Engineering Review

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2021

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Vol. 12, No. 1

119--128

EN

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.

17

Artificial intelligence-based hybrid forecasting models for manufacturing systems

Rosienkiewicz Maria

Eksploatacja i Niezawodność

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2021

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Vol. 23, no. 2

263--277

EN

The paper addresses the problem of forecasting in manufacturing systems. The main aim of the research is to propose new hybrid forecasting models combining artificial intelligencebased methods with traditional techniques based on time series – namely: Hybrid econometric model, Hybrid artificial neural network model, Hybrid support vector machine model and Hybrid extreme learning machine model. The study focuses on solving the problem of limited access to independent variables. Empirical verification of the proposed models is built upon real data from the three manufacturing system areas – production planning, maintenance and quality control. Moreover, in the paper, an algorithm for the forecasting accuracy assessment and optimal method selection for industrial companies is introduced. It can serve not only as an efficient and costless tool for advanced manufacturing companies willing to select the right forecasting method for their particular needs but also as an approach supporting the initial steps of transformation towards smart factory and Industry 4.0 implementation.

18

Computer aided assembly planning using MS Excel software – a case study

Brzozowska Jolanta, Gola Arkadiusz

Applied Computer Science

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2021

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Vol. 17, no. 2

70--89

EN

The issue of planning assembly operations remains crucial decision-making area for many of manufacturing companies. It becomes particularly significant in case of small and medium enterprises that perform unit or small-scale production, where the option of applying specialized software is often very limited – both due to high purchase price, but also due to its applicability to single unit manufacturing, that is executed based on individual customer orders. The present article describes the possibility of applying the MS Excel spreadsheet in the planning of machine assembly processes. It emphasises, in particular, the method for using the spreadsheet in subsequent stages of the process, and the identification of possible causes that have impact on problems with the planning process. We performed our analysis on the basis of actual data from one of the machine industry enterprises that manufactures in central Poland.

19

Production Scheduling for the Two Furnaces – One Casting Line System

Stawowy A., Duda J.

Archives of Foundry Engineering

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2020

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Vol. 20, iss. 1

43--48

EN

The paper presents a production scheduling problem in a foundry equipped with two furnaces and one casting line, where the line is a bottleneck and furnaces, of the same capacity, work in parallel. The amount of produced castings may not exceed the capacity of the line and the furnaces, and their loads determine metal type from which the products are manufactured on the casting line. The purpose of planning is to create the processing order of metal production to prevent delays in the delivery of the ordered products to the customers. The problem is a mix of a lot-sizing and scheduling problems on two machines (the furnaces) run in parallel. The article gives a mathematical model that defines the optimization problem, and its relaxed version based on the concept of a rolling-horizon planning. The proposed approaches, i.e. commercial solver and Iterated Local Search (ILS) heuristic, were tested on a sample data and different problem sizes. The tests have shown that rolling horizon approach gives the best results for most problems, however, developed ILS algorithm gives better results for the largest problem instances with tight furnace capacity.

20

Joint effect of forecasting and lot-sizing method on cost minimization objective of a manufacturer: a case study

Olesen Jack, Pedersen Carl-Emil Houmøller, Knudsen Markus Germann, Toft Sandra, Nedbailo Vladimir, Prisak Johan, Nielsen Izabela Ewa, Saha Subrata

Applied Computer Science

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2020

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Vol. 16, no. 4

21--36

EN

Forecasting and lot-sizing problems are key for a variety of products manufactured in a plant of finite capacity. The plant manager needs to put special emphasis on the way of selecting the right forecasting methods with a higher level of accuracy and to conduct procurement planning based on specific lot-sizing methods and associated rolling horizon. The study is con-ducted using real case data form the Fibertex Personal Care, and has evalu-ated the joint influence of forecasting procedures such as ARIMA, exponen-tial smoothing methods; and deterministic lot-sizing methods such as the Wagner-Whitin method, modified Silver-Meal heuristic to draw insights on the effect of the appropriate method selection on minimization of operational cost. The objective is to explore their joint effect on the cost minimization goal. It is found that a proficient selection process has a considerable impact on performance. The proposed method can help a manager to save substantial operational costs.