A fuzzy logic-based model for analysis and evaluation of services in a manufacturing company

Oblak, Leon; Kuzman, Manja Kitek; Grošelj, Petra

doi:10.5937/jaes15-13399

Cited by 10 publications

(9 citation statements)

References 78 publications

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“…Fuzzy logic is a system of reasoning and computation in which the objects of reasoning and computation are classes with unsharp (fuzzy) boundaries [8].The fuzzy logic allows the processing of fuzzy data, as well as the adoption of certain conclusions based on imprecise assertions and inaccurate data [9]. Fuzzy logic has been successfully used for various problems such as evaluation of services in a manufacturing company [10], as support in industrial engineering management [11].Also,there are several papers in the literature where authors applied fuzzy logic on eco-driving in order to achieve a more economical and environmentally friendly driving [12], [13], [14], [15]. In order to have active driver support system in view of eco-driving, it is necessary to clearly defi ne parameters affecting the fuel consumption and timely correct them either by advices of eco-driving instructor or by given signals fromon-board eco-driving support systems and devices.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of driver's eco-driving skills based on fuzzy logic model: A realistic example of vehicle operation in real-world conditions

Stokic¹,

Momcilovic²,

Vujanovic³

2019

J Appl Eng Science

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It is well known that fuzzy logic is a processing tool in circumstances lacking of clear linguistic information, as well as making conclusions based on imprecise assertions and rough data. Eco-driving rules that the drivers should comply with are not always made of concrete values (exact acceleration / deceleration rates, torque or headway / distance kept from the vehicle ahead, etc.), but often linguistically expressed and subjective (e.g. soft acceleration, mid-range engine speed, soft deceleration, suffi cient distance, etc.). Therefore, the authors recognized fuzzy logic potentials as an effi cient tool to overcome all mentioned barriers and thus to increase vehicle energy efi ciency and reduce emissions of harmful gases which are main goals of eco-driving. The primary objective of this paper is to raise the awareness on the potentials and effi ciency of fuzzy logic systems' use in eco-driving as a tool for achieving more ecologically & economically sustainable road transport. The rules that drivers should follow in order to achieve and maintain eco-driving goals, as well as the parameters to be monitored to evaluatedriver's behaviour i.e. the compliance with eco-driving rules are presented in the paper. The authors propose a driver rating system based on the fuzzy logic model constructed within MatLab. Within the proposed model the input parameters are actual acceleration/deceleration rates, engine speed and accelerator pedal pressure(APP) and while model output are driver ratings (scores ranging from 0 to 10 points) after completed a driving cycle. A real-world example based on data collected via vehicle OBDII connector by a TEXA logging device in realistic vehicle operation conditions. The consequent actual results of drivers' behaviour rating tool based on the proposed model are presented in the paper.

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Section: Introductionmentioning

confidence: 99%

Evaluation of driver's eco-driving skills based on fuzzy logic model: A realistic example of vehicle operation in real-world conditions

Stokic¹,

Momcilovic²,

Vujanovic³

2019

J Appl Eng Science

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“…As a result, they showed that the proposed heuristic outperforms the current method and leads to a considerable reduction in inventory. Extra research (de Kok, 1985;Tempelmeier, 2007;Selçuk & A gralı, 2013;Jaggi et al, 2016;Salemi, 2016;Oblak et al, 2017) has also been carried out to address diverse aspects of backordering and service-level constraint of fabrication systems.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modelling for a fabrication–inventory problem with scrap, an acceptable stock-out level, stochastic failures and a multi-shipment policy

Chiu

Chen

et al. 2019

Arab Journal of Basic and Applied Sciences

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“…With a help from an analytical model and the Lagrangian multiplier technique, they were able to simultaneously derive the optimal order quantity, lead time, and number of shipments to each customer per cycle. Additional studies (Fergany, 2016;Rakyta et al, 2016;Jindal & Solanki, 2016;Jaggi et al, 2016;Qu & Ji, 2016;Salemi, 2016;Oblak et al, 2017;van Rhyn & Hancke, 2017) have also been conducted to explore the effects of permitted backlogging and service level constraint on fabrication systems. Nevertheless, little attention has been paid to exploration of joint effects of machine failure, backorder of permissible shortage, rework and scrap on stock replenishing decision, and the present work is set to fill this gap.…”

Section: Introductionmentioning

confidence: 99%

Joint effects of stochastic machine failure, backorder of permissible shortage, rework, and scrap on stock replenishing decision

Chiu¹,

Chen²,

Chiu³

et al. 2019

10.5267/j.ijiec

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With the intention of addressing product quality, machine reliability, and acceptable service level issues in real fabrication systems, this paper studies joint effects of stochastic breakdown, backorder of permissible shortage, rework, and scrap on the optimal stock replenishing policy. A decision model is developed to solve the problem, which consists of mathematical modeling, formulations, and optimization method in order to help analyze the problem, derive the system cost function, and find the optimal replenishment cycle length decision. Applicability of the research results are demonstrated by a numerical example. The proposed decision model enables production managers to not only determine the optimal stock replenishing policy, but also reveal individual impact and/or joint effects of stochastic breakdown, defective rate, backorder of allowable shortage, rework, and scrap on the replenishing decision. With such an in-depth study, diverse system characteristics become available for managerial decision-making.

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A fuzzy logic-based model for analysis and evaluation of services in a manufacturing company

Abstract: In an increasingly competitive market, companies must look for new ways to gain

Cited by 10 publications

References 78 publications

Evaluation of driver's eco-driving skills based on fuzzy logic model: A realistic example of vehicle operation in real-world conditions

Evaluation of driver's eco-driving skills based on fuzzy logic model: A realistic example of vehicle operation in real-world conditions

Mathematical modelling for a fabrication–inventory problem with scrap, an acceptable stock-out level, stochastic failures and a multi-shipment policy

Joint effects of stochastic machine failure, backorder of permissible shortage, rework, and scrap on stock replenishing decision

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