Review evolution of cellular manufacturing system’s approaches: Human resource planning method

32 Fig. 1. A Flow Diagram of worker assignment in a Cellular Manufacturing System 1.1 Optimum Number of Workers Perhaps, finding the optimal number of workers is the main idea of investigating HRM in CMS. To determine optimal number of operators and part assignment, Park and Lee (1995) developed a 2-stage model while in first stage, a Taguchi method was used to determine system performance which was then used as objective function of assigning model. The idea of maximizing saving costs between operation and outsourcing costs was investigated by Heady (1997). But their model did not investigate operator level, training, hiring and firing costs. Norman et al. (2002) proposed a model to assign workers in manufacturing cells in order to maximize the system profit. Ertay and Ruan (2005) developed the idea of determining number of operators for maximizing number of outputs. For this purpose, using weighted input data, a data envelopment analysis (DEA) was applied. But in the proposed model, the same skill for all operators and machines was considered. 1.2 Promoting and Assigning Skilled Workers Since in real industries, operator’s skill are not same, so their outputs will not be the same. The idea of considering operator levels was investigated by Suer and Cedeño (1996). For this purpose, a mixed integer programming method was used to generate alternative operator levels and then another integer programming is employed to find the optimal operator assignments to the cells. Askin and Huang (1997) used integer programming for assigning workers to cells in order to determine a training program for employees. Aryanezhad et al. (2009) considered 3 skill levels for workers, which can be promoted through the planning horizon by training. Then a multi-period scheduling model was developed for simultaneous cell forming and worker assignning. Jannes et al. (2005) focused on assiginings workers to team works with the aims of minimizing training and assigning costs as well as maximizing labor flexibility. In the same year, Fitzpatrick and Askin (2005) argued that elemens of a good team formation is not limited to personnal skills and characteristics but technological and human interactions. Hence, by using pre-determined skill level measures, they tried to select workers and assign them to appropriate teams in cells to maximize team performance. Cesaní and Steudel (2005) focused on some factors on deployment of labors. Then, they focused on work sharing, work balancing and leveling the operator assignments (in presence of bottleneck operations). To prevent overloading and over-assigning of operators, Satoglu and Suresh (2009) used goal programming in a mathematical model where the objectives were minimizing over assignment of workers, cross training, hiring and firing costs. 1.3 Cross-trained workers Note that cross-trained workers are refered to those workers that are trained to perofrm more than one task. Determinining best sets of crosstraining workers can improve system performance with more flexibility. Bartholdi and Eisenstein (1996) found that by using large work cells with multiple workstations and workers, a stable partition and assignment of work will spontaneously emerge that cause balance production lines and maximize the production rate. Kleiner et al. (1998) assumed a typical skilled workers, which can perform multi tasks with multifunctional machines, in a a computer based system. Other attributes of the proposed model were included cell lead time, part travel distance, A. Delgoshaei et al. / Journal of Project Management 4 (2019) 33 process yield, operator classification and labor efficiency. In continue, Gel et al. (2000) showed that cross-trained workers can achieve higher performance than normal workers. As a different point of view, Askin and Huang (2001) studied the performance of greedy, beam search, and simulated annealing for a multi-objective optimization model for the formation of worker teams and a cross-training plan for cellular manufacturing. Olorunniwo and Udo (2002) showed that top management role and employee cross-trained have significant impact on the successful implementation of CMS. Kher (2000b) focused on training schemes that obtained by using cross-trained workers under learning, relearning, and attrition conditions. The idea of distributing skilled workers within teams and the degree of workforce belongs to Molleman and Slomp (1999) where they indicated the mentioned items have significant impact on system performance. Their findings showed that a uniform distribution of workforce skill resulted better system performance and consequently each worker should master the same number of tasks. Later, Slomp and Molleman (2000) compared four cross-training policies based on the workload of the bottleneck worker in both static and dynamic circumstances. The results confirmed that better team performance can be expected by using higher levels of cross-training workers. Jensen (2000) involved with staffing level and shop layouts in departmental, strictly and hybrid cell layouts. By changing number of employees in each department and considering 3 levels of workload balance and 2 labor transferring rules, they evaluated flow time, mean of tardiness and square mean of job tardiness. Li et al. (2012) focused on minimizing average salary while maximizing average of satisfaction. For this purpose they developed a multi-objective mixed integer programming to determine number of cross-trained labors and also tasks that must be assigned to the labors in flexible assembly cell layout. Another contribution of their research was considering worker’s satisfaction and task redundancy levels. 1.4 Dual Resource Problems Dual constraint resource problems refers the problems where scheduling parts on machines and workers simultaneously. Kher (2000a) has investigated training schemes obtained by cross-trained workers under learning, relearning, and attrition conditions. Kher et al. (1999) further conclude that the effectiveness of cross-training depends significantly on the existing forgetting rate of the workers. In addition, they remarked on the significant relationship between batch size and worker flexibility cross-training include variability, labor interaction, resources utilization and transition efficiency. Molleman & Slomp (1999)indicate that the distribution of skill within teams and the degree of workforce multi-functionality have a significant impact on system performance. Their findings indicate that a uniform workforce skill distribution resulted in better system performance. In other words, each worker should master the same number of tasks. Xu et al. (2011) provided a novel research in dual resource systems. Hamedi et al. (2012) developed a model where parts, machines and workers are grouped and assigned to the generated virtual cells simultaneously. In continue, the developed model is solved through a multi-objective Tabu Search algorithm to find near optimum solutions. 1.5 Uncertain Market Demands The idea considering dynamic part demands in HRM-CMS which can cause system imbalance is less developed. To solve this problem, Mahdavi et al. (2010) developed an a multi-mode planning model for assigning workers to cells in a reconfigurable CMS. In the proposed model, hiring, firing and also salary costs were considered as a part of total system costs. Another contribution of their model was considering available time for workers. As described in pervious section, Mahdavi et al. (2012) focused on inter-cellular movements of workers and parts while processing on specific machine. Min and Shin (1993) considered the skilled human resource as a part of cell forming process. Their objective was finding machine operators with similar expertise and skills to produce similar part families. Black and Schroer (1993) investigated a case where multi-functional operators can walk within cells to complete operations. They reported that using portable work stations can increase the output rate. Morris and Tersine (1994) examined the impact of labor and equipment in a dual constraint resource planning to compare the process layouts and cell layouts. Hyer et al. (1999) carried out a filed study considering 8 human factors in cell systems to find the importance of different human factors may influence the CMS. As a result they concluded that communication and tem work ranked as the most important factors in 34 utilizing the cell systems.Cesaní and Steudel (2005) developed a 2 phase frame work for worker assignment in CMS based on human resource factors. In the first phase, they performed an empirical investigation to find important factors that affect the labor flexibility. In second phase they used these factors to find optimum worker assignment in cells. The contribution of their research is finding balance between the operators’ workload, the level and type of machine sharing to increase the performance of cell based systems. Chakravorty and Hales (2004) provided a case study to survey the impact of worker assignment on system performance in a manufacturer and supplier of residential and light commercial building products. Afterward, Chakravorty and Hales (2008) reported that during early stage of working after forming cells, both technical failures and human resource errors are existed. However, after spending a period although the technical problems may reduce but the human resource problems are still exists which must be managed to reduce the harms. Yu et al. (2014) focused on minimizing total labor hour while maximizing throughput time of products in a line-cell conversion problem. They found that implementing the proposed method can increase the workforce motivation. Jannes Slomp et al. (2005) proposed a new method which considered labor grouping as well as machine part grouping during the cell forming process. The contribution of their research is focusing on balanced loads for workers, minimization of inter-ce