Combining Kansei Engineering and Artificial Neural Network to Assess Worker Capacity in Small-Medium Food Industry

This paper highlighted a new method for worker capacity assessment in Indonesian small-medium food industry. The sustainable and productivity of Indonesian food industry should be maintained based on the workers capacity. The status of worker capacity could be categorized as normal, capacity constrained worker and bottleneck. By using Kansei Engineering, worker capacity can be assessed using verbal response of profile of mood states, non-verbal response of heart rate in a given workplace environmental parameters. Fusing various Kansei Engineering parameters of worker capacity requires a robust modeling tool. Artificial Neural Network (ANN) is required to assess worker capacity. The model was demonstrated via a case study of Tempe Industry. The trained ANN model generated satisfied accuracy and minimum error. The research results concluded the possibility to assess worker capacity in Indonesian small-medium food industry by combining Kansei Engineering and ANN

Development of Green-Affective Work System for Food SMEs

Work system of food Small and Medium-sized Enterprises (SMEs) is influenced by various factors as worker performance, characteristics of raw material, value-added process and workplace environmental ergonomics. Green-affective design analyzes properties of work systems and how these technical attributes could be sensible to the environment (Green) and worker (Affective). The research objectives were: 1) To explore the relationship between green and affective parameters in work systems of Food SMEs; 2) To design a green-affective work system for Food SMEs. Six (6) SMEs of different food products were used for the case studies as Crackers, Nuggets, Fish Chips, Bakpia, Tempe and Herbal Instant Beverages. Air conditioner was suggested to set the temperature set points for controlling environmental ergonomics. Green parameters were analyzed using calculation of air conditioner electricity cost at different workplace temperature set point. Affective parameters were analyzed using heart rate, worker energy consumption and rowan incentive plan. Research findings indicated air conditioner could be used to control environmental ergonomics based on the satisfied temperature set points and efficient electricity cost in work system of food SMEs