An Intelligent Incentive Model Based on Environmental Ergonomics for Food SMEs

Abstract

In this study, an intelligent incentive model based on environmental ergonomics in food small and medium-sized enterprises (SMEs) was developed. Environmental ergonomics was defined as the impact of temperature and relative humidity within a certain range on a worker's heart rate during work. Optimum environmental ergonomics are highly required as a basic standard for food SMEs to provide fair incentives. Recommendable parameters from a genetic algorithm and fuzzy inference modeling were used to model customized incentives based on optimum heart rate, workplace temperature and relative humidity before and after working. The research hypothesis stated that industries should optimize their workload and workstation environment prior to customizing incentives. The research objectives were: 1) to recommend optimum environmental ergonomics parameters for customized incentives; 2) to determine the incentives at workstations of SMEs based on optimum environmental ergonomics parameters and fuzzy inference modeling. The optimum values for heart rate, workstation temperature and relative humidity used were based on recommendable values from the genetic algorithm. An inference model was developed to generate decisions whether a worker should receive an incentive based on a calculated index. The results indicated that 84.4% of workers should receive an incentive. The results of this research could be used to promote the concept of ergonomicsbased customized incentives.

Modeling SMEs’ Trust in the Implementation of Industry 4.0 using Kansei Engineering and Artificial Neural Network: Food and Beverage SMEs Context

“…Figure 1 depicts the conceptual model of SMEs' trust in the implementation of Industry 4.0 using Kansei Engineering. The methodology of Kansei Engineeringtype II as Kansei Engineering system was selected due to its capability to model SMEs [6][7][8]. The conceptual model was adapted from Lee and See [5] and Ushada, et al [4].…”

“…Trust can be influenced by several other Kansei parameters, such as knowledge, familiarity, agreement and preference [4,5]. Some Kansei parameters have been evaluated for food and beverage SMEs, such as workload [6], environmental ergonomics [7] and work incentives [8]. However, these parameters were utilized in the context of ergonomic workplace design.…”

“…The function of the Kansei Engineering method is to quantify Kansei words as measurable parameters. Kansei Engineering has been used in industry due to its capability to analyze human mentality parameters in product areas [9,10], service areas [11,12], information technology [13], and system development [6][7][8].…”

Development of Kansei Engineering-based System for Agro-industry (KESAN) for Worker Trust Assessment in Food Small Medium-sized Enterprises

“…Trust was difficult to assess due to a complex problem and difficult to understand. Kansei, or known as affective states, were essential parameters for the user in product design and development (Ushada and Murase, 2009) and workers in a working system and ergonomic design (Zhou et al, 2017;Ushada et al, 2019). Method of Kansei Engineering has been used to derive some abstractive parameters as satisfaction and trust .…”

“…Mechanism of attributes definition referred to our previous research(Ushada et al, 2012) based on the specific industrial needs of the system as appropriate technology. The questionnaire for user acceptance test was developed and inspired by the questionnaire of previous research for KESAN of workload monitoring device(Ushada et al, 2019), and environmental ergonomics control(Agassi et al, 2019). The questionnaire was pursued on 110 respondents of Food and Beverage SMEs which classified in 3 categories as 1) twenty five Professional manager of SMEs, 2) twenty five University students which own start-up of SMEs, 3) sixty senior students who attended the class of ergonomic and product design and development since they knew and familiar with ergonomic and industry 4.0.…”