Mathematical Models for Manufacturing Systems Capacity Planning and Expansion – An Overview

Gola, Arkadiusz; Relich, Marcin; Kłosowski, Grzegorz; Świć, Antoni

doi:10.4028/www.scientific.net/amm.791.125

Cited by 9 publications

(4 citation statements)

References 11 publications

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“…Moreover, designing manufacturing systems at the outset of change also requires consideration of long-term demand scenarios, which in most cases involves a high degree of uncertainty related to, e.g., timing of new product designs, demand volume levels, or volatility of demand (Wiendahl and Heger, 2004). These uncertainties are important determinants for the attractiveness of changeability and reconfigurability, due to the ability to respond more efficiently to unforeseen changes in functionality and capacity (Gola et al, 2015).…”

Section: Design For Changeability and Reconfigurabilitymentioning

confidence: 99%

Evaluating the investment feasibility and industrial implementation of changeable and reconfigurable manufacturing concepts

Andersen¹,

Brunoe

Nielsen³

et al. 2018

JMTM

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Purpose The purpose of this paper is to present a decisions support tool that can be applied in initial stages of design, for evaluating the investment feasibility of changeable and reconfigurable manufacturing design concepts, based on future demand predictions and their uncertainties. A quantitative model is proposed, which evaluates the discounted value of capital and operating costs of changeable manufacturing design concepts, based on essential characteristics regarding their type and extent of changeability. Design/methodology/approach Quantitative empirical modeling is applied, where model conceptualization, validation, and implementation are central elements, using two Danish manufacturing companies as cases. Findings The applicability of the model is demonstrated in the two case companies, highlighting differences in type, extent, and level of feasible changeability, as a result of differences in product and production characteristics. Research limitations/implications Further studies of changeability implementation should be conducted across industrial fields in order to generalize findings. Practical implications There is currently limited support for the conceptual design phase of changeable and reconfigurable manufacturing, where critical decisions regarding type, extent, and level of changeability must be made, regardless of high degrees of uncertainty about future demand scenarios. Originality/value This paper expands previous research on design for changeability and reconfigurability, by explicitly considering changeability as a capability that can be enabled in various ways for various purposes in different industrial contexts. The proposed model and the case implementations provide important knowledge on the transition toward changeability in industry.

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Section: Design For Changeability and Reconfigurabilitymentioning

confidence: 99%

Evaluating the investment feasibility and industrial implementation of changeable and reconfigurable manufacturing concepts

Andersen¹,

Brunoe

Nielsen³

et al. 2018

JMTM

View full text Add to dashboard Cite

show abstract

“…High frequency of launching new products, changing production volumes and demand fluctuations are the most frequent problem that companies face [3]. To do this and to keep the pace of technological, economic and social changes, which have a significant impact on the progress in the organization of production, the company must react in a cost-effective, efficient and fast way [4][5].…”

Section: Introductionmentioning

confidence: 99%

Simulation Based Analysis of Reconfigurable Manufacturing System Configurations

Gola

Świć

2016

AMM

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Nowadays, manufacturers seek customers’ satisfaction by increasing products variety and customization while striving for agility and productivity. To remain competitive, companies must design manufacturing systems that not only produce high-quality products at low cost, but also respond to market changes in an economical way. One of the critical problems of manufacturing systems design is to decide which of possible configurations is the most advantageous for a company. This article presents the possibility of using simulation methods in the process of analysis of possible configurations of Reconfigurable Manufacturing System according to maximization the productivity of the system.

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“…PDM is part of product lifecycle management (PLM) that allows manufacturing companies to manage their products throughout their lifecycles, from the idea generation of a new product, its development and manufacturing, to disposal [12,13]. PLM represents connection between CAD, digital manufacturing, and simulation, as well as the virtual world and interfaces with the ERP system supporting the physical side of modern manufacturing along the supply chain [14,15].…”

Section: Introductionmentioning

confidence: 99%

Computational Intelligence for Estimating Cost of New Product Development

Relich

2016

Foundations of Management

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The main aim of the work is to assess physical parameters of forest woodchips and their impact on the prices achieved by the supplier in transactions with a power plant. During fragmentation of logging residue, high content of green matter and contaminants negatively impacts the quality parameters that serve as basis for settlements. The analysis concerns data on the main parameters -water content, fuel value, sulphur and ash content -from 252 days of deliveries of forest chips to a power plant. The deliveries were realised from forested areas on an average about 340 km from the plant. Average water content and the resultant fuel value of forest chips was within 27-47% and 8.7-12.9 GJ×Mg −1 (appropriately), respectively. They depend on the month in which they are delivered to the power plant. The threshold values for the above-mentioned parameters are set by the plant at a real level and the suppliers have no problems with meeting them. The parameter that is most frequently exceeded is ash content (11.5% of cases). The settlement system does not differentiate on the basis of the transport distance but gives possibility to lower the settlement price when the quality parameters are not met but provides no reward for deliveries with parameters better than the average ones. On the basis of results obtained, it was calculated that average annual settlement price is lower than the contract price by about 0.20 PLN×GJ −1 , which in case of the analysed company may translate into an average daily loss of about 700 PLN.

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Mathematical Models for Manufacturing Systems Capacity Planning and Expansion – An Overview

Cited by 9 publications

References 11 publications

Evaluating the investment feasibility and industrial implementation of changeable and reconfigurable manufacturing concepts

Evaluating the investment feasibility and industrial implementation of changeable and reconfigurable manufacturing concepts

Simulation Based Analysis of Reconfigurable Manufacturing System Configurations

Computational Intelligence for Estimating Cost of New Product Development

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