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Attention this is the Title Please Use Bold and Capital-Initials

Anna Smith1* Xinzhou Song2
  • School of Management, Northern Canada University, PO box 1178, Toronto M3A 2K7, Canada
  • School of Economics, Peking University, 176 Zhong Guan Cun Street, Beijing 100086, China
* E-mail of the corresponding author:

This paper is just a sample template for the prospective authors of IISTE Over the decades, the concepts of holons and holonic systems have been adopted in many research fields, but they are scarcely attempted on labour planning. A literature gap exists, thus motivating the author to come up with a holonic model that uses exponential smoothing to forecast some quantitative variables in labour-intensive production. These varying parameters include the machine utilisation that reflects the demand and the worker absenteeism and turnover that constitute the disturbance. Collective equations are formulated to periodically compute the number of workers required. For model validation purpose, twenty-four-month data analysis is conducted on a mock-up basis. Keywords: key words, orkforce sizing, job-shop production, holonic model

1. Introduction
In the manufacturing sector today, human capital is still essential for most factories to carry out a variety of manual operations, in spite of the rapid advancement of automation technology and robotics. Futuristic vision of “unmanned manufacturing� (Deen 1993) is forbiddingly expensive, because all its hardware components need to be computer controlled so as to freely communicate with each other; and yet, most of the outcomes are not promising (Sun & Venuvinod 2001). By and large, factories equipped with relatively simple machinery controls will require continuous attendance of human operators; for examples, textile mills, leather products, and medical appliances. With limited capital investments in production equipment, the main budget of their fixed costs lies on the workforce size (Techawiboonwong et al. 2006).

With regard to cost-effectiveness, labour planning always opts for the minimum amount of workers needed to deal with the daily operations, as well as the probable rate of disturbance (Lim et al. 2008). The workforce disturbance is often ascribed to absenteeism and turnover, which may result in considerable loss of productivity for any labour-intensive division (Easton & Goodale 2002). Buffering with redundant skilled workers (Molleman & Slomp 1999) or relief workers (Redding 2004) might be a direct solution to absenteeism; however, the rising labour cost must be justifiable due to the fact that underutilisation of labour during low demand seasons is considered a waste of resources. Absenteeism is the measure of unplanned absences from workplace due to some reasons like personal emergency, accident, illness, etc. Turnover occurs when an active worker resigns from the company of his own accord, thus leaving a vacant post until a replacement is found. If such disturbance has caused a large number of tasks become unattended and overdue, the company is then vulnerable to overtime cost, shrunk capacity and productivity, extra queuing time, lost business income, etc. In order to prevent these deteriorative effects, optimising the number of workers can be helpful. As a fundamental branch of knowledge in manufacturing business, workforce management will never fall behind the times. Therefore, it is worth an attempt to incorporate a novel methodology, such as HMS, into the state of the art of workforce sizing.