Production Planning Incorporate with Job Rotation and Work

Thesis/Project Title: Production Planning Incorporate with Job rotation and Work Injury by Multi-Objective Criteria

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Table of Contents

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1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.1. Background and Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2. Research Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2. OBJECTIVES AND SCOPE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3. LITERATURE REVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.1 Production Planning and Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.2 HUMAN FACTOR IN PRODUCTION PLANNING . . . . . . . . . . . . . 9

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3.2.1. Human Scheduling in Technical System . . . . . . . . . . . . . . . . . . . . . . . 10

3.2.2. Human Work Related Injuries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

3.2.3. Leading Factors for Work Injuries . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.2.4. How We Reduce Work Injuries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

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3.3 QUALITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.3.1. Manufacturing Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.3.2. Dimensions of Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3.4 JOB ROTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

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3.4.1. Importance of Job Rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.4.2. Outcomes of Job Rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.4.3. Job Rotation as a Cost Effective Tool . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.5 WORK FORCE AGING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

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3.5.1. Aging Effect Worker Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.5.2. Workforce Aging Effect on Production Performance . . . . . . . . . . . . . 15

4. METHODOLOGY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
5. CONCLUSION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
6. TIMELINE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
7. REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

1. INTRODUCTION

1.1 Background and Motivation

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In the last few years, the question of human well-being at the working place has come afore as a key issues in production planning and scheduling. The manufacturing productivity is affected by both the human and machine factors. However, much of the previous research has been focused on the machine aspect but the human aspect. The previous work considers not only the productivity but also the production cost, worker safety and machine utilization. Particularly, (Xu, 2015) demonstrated the significance of work injury to the total production cost. His work also showed that the effect of work injury can be reduced by designing a production system.

Due to the increasing cost of work injuries as well as concern of health work place, both the government and industry have made an effort on preventing work injury occurrences. In 2005, the government of Canada paid approximately $6.8 billion dollars in benefits through its Workers‟ Compensation Boards (WCBs) organization. It is being realized that the cost incurred by work injuries contributes a large portion to the total production cost, and strategies are urgently required to tackle the problem of work injury. In 2000 to 2012 period, the total costs of occupational injuries to the Canadian economy was estimated to be more than $19 billion annually.

The factors other than the production system design, which lead to work injury, are: employee boredom, fatigue, lack of motivation, lack of training, and mismatch of job and workforce age. Besides design of production systems, to remove or solve the issues related to work injury, there are three kinds of techniques: Engineering solutions, Administrative solutions and Personal safety equipment (Tayyari & Smith, 1997).

Job rotation comes in the category of administrative solution. It is about the rotation of workers among a number of non-similar workstations, where each worker requires different skills or techniques and responsibilities to do job (Azizi, Zolfaghari & Liang, 2010). It enables operators to become multi-skilled by providing them with a greater ability to handle increased demand and large product variability (Michalos et al., 2010). When many jobs of different requirements and workers of different capabilities are involved, the job rotation problem becomes very complex.

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Due to the complexity of job rotation, there are implications of job rotation as well. If not done properly job rotation can increase the cost of production and also reduce the quality of the manufacturing system. Cost is a factor which is widely understood and studied but Quality is one of the most important but the least understood attribute of a system. Without quality, a system cannot comply with required goals and standards.

Conventionally, production planning is mainly about materials resource planning. The materials include both the material for products and the machine tools for production of the products (Krajewski et al., 2005). Many techniques have been established to improve the effectiveness of production planning, to make a plan which meets the customer demand, satisfaction and cost with other features such as continuity and resilience of a system as referred to by Zhang and Lin (2010). Zhang defines resilience as a system’s post-damage property – i.e. the system’s ability to recover its function from some damage. In the context of enterprises, Guelfi et al. (2008) defined the resilience as the capacity of a business process to recover and reinforce itself when facing changes. This calls for a scientific approach to solving this problem.

1.2 Research Questions

The following questions come up:

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Question 1:

How may job rotation significantly affect the cost of production especially with its connection to work injury (particularly related to the worker aging)?

Question 2:

How to define and model the quality of the operation of a manufacturing or production system particularly in terms of resilience or system disruption?

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Question 3:

How to define and model job rotation in production planning and scheduling so as to make a balanced improvement in terms of the cost and resilience?

2. Objectives and Scope

Objective 1

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To model the job rotation for incorporating them into the production planning and scheduling. The model should consider the influence of job rotation to work injury (due to aging).

Objective 2

To develop a model for the resilience of a production system with planning and scheduling in place. The resilience may simply refer to operation disruption. It is assumed that by meeting the customer requirement for products or jobs, the quality of a production system is guaranteed. It is also assumed that the product delivery time is satisfied by an effective production plan and schedule.

Objective 3

To develop a production planning model for achieving the lowest cost and highest resilience. In this model, besides the decision variables such as production quantity, the variable for job rotation will be included.

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3. Literature Review

3.1 Production Planning and Scheduling

Production planning is a planning of production and manufacturing modules in any organization or industry. It utilizes the allocation of resources (employees, material and machines) in order to achieve the organizational goals. On the other hand production scheduling differs from production planning in that a schedule includes the information such as what system components (machines and/or humans) do what jobs at what times. Ideally, one may want to be the best for all the foregoing goals but in reality this is not possible as there may be conflicts among them. For instance, low cost production may likely lead to poor product quality. Nevertheless, an optimal trade-off among these elements does make sense. In fact, from a mathematical point of view, the problem is inherently a multi-objective optimisation problem. In practice, the multi-objective optimization problem is modeled as a single objective optimization problem while the rest of elements are considered as constraints or only implicitly assumed. For instance, often the quality is assumed to be fine as long as the production meets the quantity, and the time is implicitly represented in a way that the customer demand for a period of time say T is divided into a series of time segments (t_i), and then on each time segment (t_i), there will be the product quantity say d_i. Based on the foregoing discussion, the quality, quantity, and time are modelled. This research will further consider cost and resilience.

The cost goal is conventional in the mathematical model for production planning and scheduling (Cramer, 2011). Elements that incur the cost are: material cost, machine utilization cost, human cost, human work injury cost, inventory cost, penalty cost, overhead cost, and so forth (Phruksaphanrat, Ohsato & Yenradee, 2006; Swamidass, 2000; Gallego, 2001; Xu, 2015; Sule, 2008). The resilience goal is less known to the literature especially a joint consideration of the cost goal and resilience goal. There are some works on job rotation, which are categorized into the human factors in planning and scheduling, and will be discussed later in this document.

Broadly, according to (Laperrière et al., 2014) Production planning does not work alone, it normally approaches with other production activities (Fig. 1) such as aggregate production planning, production scheduling and production control. Aggregate Production Planning (APP) determines what, when and how much the work force levels, inventory status and production rate required to achieve the market or customer demand. APP falls between the broad decisions of long-range planning and the highly specific and detailed short-range planning decisions (Chakrabortty & Hasin, 2013).Production Scheduling determines the sequence of production for planned products on daily and weekly basis (Pinedo, 2005); see also the previous discussion. Production Controldeals with the real time information from the processes such as workforce and inventory level to take decisions to remove or avoid the system from disruption (Pinedo, 2005). In this thesis research, the scope is production planning and scheduling.

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3.2 Human factors in production planning

Technological developments in the production system allowed the automation of the manufacturing processes and assembly lines, but employees or human operators still remain a serious factor in every production system (Chryssolouris, 2006). Employees or workers are the most important resources of any organization. The way in which workers are allocated to tasks can meaningfully affect a company’s performance or productivity (Tharmmaphornphilas & Norman, 2007). Therefore non-compatibility or mismatch of humans to technical systems may even cause injuries in the humans, which is the main concern of human factor engineering in production planning. To solve this problem, job rotation is the best technique to overcome this issue and it helps to increase the production efficiency or productivity (McKay & Wiers, 2006).

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3.2.1 Human Scheduling in Technical System

Presently, industries assign tasks to employees according to their competence, skills or experience. This method helps to increase the system productivity and quality but it can results in worker to be assigned same task every time (Tharmmaphornphilas & Norman, 2007). Performing the repetitive tasks may reason for musculoskeletal disorders, accrue stress, induce boredom, create fatigue and may lead to occupational illness and injury (Hagberg et al. 1995).

3.2.2 Human Work Related Injuries

The behavior of a worker can be affected by several factors such as: (Digiesi, et al. 2009).

• Work Environment: (physical: microclimate, ergonomics, noise; social: human relationships, communication among the group).
• Nature of the Task: (discrete vs. continuous, repetitive vs. non-repetitive, motor vs. cognitive).
• Personal factors: (psycho-physical attitude, personal skill, age, sex).

3.2.3 Leading Factors for Work Injuries

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It has been noticed that there are some major factors which contributes to work injuries are:

• Employee Boredom: It can be related with performance reduction, general dissatisfaction, and accidents (Azizi, Zolfaghari & Liang, 2010).
• Fatigue: Accumulation of fatigue causesmusculoskeletal disorders(Asensio-Cuesta et al., 2012)
• Repetitive Motions: Monotonous repetitive work has been identified as a major cause of work load related disorders (Michalos et al., 2010)
• Workforce Aging: In very repetitive short cycle operations, work-related musculoskeletal disorders tend to be more dominant in workers aged from 40 to 60 (Boenzi, et al., 2015).

3.2.4 How We Reduce Work Injuries

There are three ways to reduce or overcome the work injuries (Tayyari & Smith, 1997) .These are as follows:

• Engineering Solutions: It includes to redesign the work place, redesign tools and redesign job.
• Administrative Solutions: It includes the reconsideration of work schedules, workers rotation and career changes.
• Personal Protective Equipment:It includes safety shoes, hats, safety glasses and safety clothes.

3.3 Quality

Quality is important property of any systems and usually refers to the degree to which a system lives up to the expectation of satisfying its requirements (Ivan et al. 2014). The definition of quality, standardized by the American National Standards Institute (ANSI) and the American Society for Quality Control (ASQC) in 1978, is “the totality of features and characteristics of a product or service that bears on its ability to satisfy given needs.” This definition suggests that we must be able to identify the features and characteristics of products and services that determine customer satisfaction and form the basis for measurement and control.

3.3.1 Manufacturing Quality

In terms of manufacturing based quality, (Crosby, 1979) defined manufacturing quality as “quality is about conformance to requirement.”

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3.3.2 Dimensions of Quality

Garvin (1988) and Grady (1992) described the dimensions for quality analysis in their book are: Performance, Reliability, Conformance, Durability, Serviceability, Usability, Functionality and Supportability. Quality is often characterized in terms of attributes for system quality such as modifiability, durability, predictability (Ivan et al., 2014).

3.4 Job Rotation

Job rotation is about the rotation of workers among a number of non-similar workstations where each worker requires different skills or techniques and responsibilities to do job (Azizi, Zolfaghari & Liang, 2010). In other words job rotation can be defined as working at different operations or in different positions for particular set periods of time in a planned way (Jorgensen, 2005).

3.4.1 The Importance of Job Rotation

Implementing Job Rotation as a manufacturing method is beneficial to increase production efficiency, operator satisfaction and helps to reduce Work-related musculoskeletal Disorders (WMSDs) and labor cost (Cramer, 2011). Job rotation using lateral transfers allows employees to gain a wide range of knowledge, skills and competencies (Jorgensen, 2005). It provides a benefit or increase the firm’s ability to deal with change (Kher et al., 1999). As a benefit of job rotation to workers, it may increase worker’s job satisfaction (Cunningham and Eberle, 1990). Job rotation also yields such benefits to workers as reducing the injuries due to performing repetitive tasks as well as the worker’s fatigue especially if the worker is exposed to various muscular loads during task operation in manufacturing (Hinnen et al., 1992; Henderson, 1992). Carnahan et al. (2000) studied several methods to integrate the safety criteria into scheduling algorithms to produce job rotation schedules that reduce the potential for work injury. Job design related applications began to take shape with a scientific management approach in the 1900s. The study of management scientists such as Taylor and Gilbreth on the subject of job design becomes a foundation for scientific management. Further, many models were developed, which are associated with job design, social information processing and job characteristics approach by Hackman and Oldman in 1976 (Hackman & Oldham, 1976) and these models have enormously important effects on increasing the productivity of human resources.

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Job rotation prevents musculoskeletal disorders, eliminates boredom and increases job satisfaction and morale. As a result, an organization gains a skilled and motivated workforce, which leads to increases in productivity, employee loyalty and decreases in employee turnover (Asensio-Cuesta et al., 2012). Job rotation is considered as an appropriate organizational strategy to reduce physical workload (Paul et al., 1999; Boenzi et al., 2015) in human-based production systems and it is the most wide spread labor flexibility instrument in the case of repetitive assembly tasks (Paul et al., 1999).

3.4.2 Outcome of Job Rotation

3.4.3 Job Rotation as a Cost Effective Tool

There are several appealing factors for job rotation but one major factor is the relatively low implementation cost. Job rotation policy is very effective tool to overcome or minimize the work injuries cost or helpful in reduction of repetitive tasks, which leads to work injuries. Job rotation itself cost effective to apply in any organization the cost which only related to job rotation is training cost.

3.5 Work Force Aging

The phenomenon of population aging affects the ageing of work force which determines work force availability. Industrial and academic research are required to investigate the influence of workforce aging in formulating new working time models and job rotation planning solutions. Field investigations on the effect of workers aging on production performance were carried out at the BMW’ plant in Dingolfing, Bavaria (Loch CH et al., 2010).

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3.5.1 Aging Effects on Worker

According to (Tokarski, 2011) aging affects the worker’s performance in three aspects are:

• Physically: (physiological, perceptual and motor processes, and declines in abilities, such as dexterity, strength and endurance.
• Cognitive: (Decision making Skills, Learning skills and forgetting phenomena)
• Emotions:(Boredom, fatigue and lack of motivation)

3.5.2 Workforce Aging Effect on Production Performance

Changes in workforce age structure may have an impact on production system performance or productivity. According to Sülzenbrück et al. (2010) age-related impairments have a negative effect on working capacity and productivity. In assembly lines the higher the average age of the assemblers, the higher the risk they cannot meet all the requirements (Buck & Dworschak, 2003). The effects of ageing on employee’s physical and cognitive performances negatively affects the flexibility of human based production system (Boenzi et al., 2015).

The factors which may affect the performance of a worker with respect to ageing are:

• Muscular Strength.
• Dynamics Actions.
• Endurance (Aerobic Capacity).
• Reaction Time (Responses).
• Awkward Postures (Flexibility).

4. Proposed Methodology

• A mathematical model will be developed in terms of Production cost.
• Components of production cost will be work injury cost, work injury prevention cost, inventory cost and conventional production cost.
• Different Scenarios will be developed considering workers of different age groups and how they can be rotated between job positions, when there is a work related injury to one of them.
• When scenarios are made, mathematical model formulated in the earlier step will be applied on the scenarios.
• The mathematical model for each scenario will form the basis for the use of Multi Objective Genetic Algorithm (MOGA).
• This Aggregate production planning problem emphases on developing a Multi objective Genetic Algorithm (MOGA) method to find the optimum production plan for meeting forecasted customer demand by controlling the work injury during the production.
• Multi objective function will be inserted along with its constraints.
• A general description of steps for implementing MOGA are as follows:

• Step 1: Generate random population of n chromosomes (suitable solutions for the problem)
• Step 2: Evaluate simultaneously the Multiple fitness f(x) of each chromosome x in the population
• Step 3: Create a new population by repeating four steps (Selection, Crossover, Mutation and Acceptation) until the new population is complete.
• Step 4: Use new generated population for a further run of algorithm
• Step 5: If the stopping condition is satisfied, stop, and return the best solution in current population
• Step 6: If the stopping condition is not satisfied then go to step 2 & follow loop.

• MOGA parameters will then be inserted.

Assumptions

1. No worker is working on full capacity. It is assumed that a worker only utilizes 60 percent of his/her work capacity to fulfil the job requirement.
2. Material is always available during production.
3. Trivial solutions will be ignored.
4. No hiring and lay off during the planning horizon.
5. It is assumed that age is not a contributing factor towards work injury.

5. Conclusion

There has been some work done on the concept of production planning in terms of work injury cost. But upon doing literature review, I realized that there has been no work done when it comes to applying work injury cost and job rotation to make a production plan.

My work will focus on developing a production model by considering work injury cost and job rotation. There are quite a few benefits of this approach. Firstly, it will give us a model where workers of different age can be used in an optimized way in a production based environment. Secondly, in case of any absentee or injuries, an organization can develop a plan in such a way that workers of older age (above 50) are minimally exposed to physically intensive work.

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Furthermore, a model for job rotation will be made considering age of the workers so as to reduce work injury by minimal exposure of aged work force to physically demanding work.

Lastly, due to application of work injury and job rotation, a cost effective way to model and run a production line (in terms of manual labor) will be done.

6. Timeline

7. References

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3. Chakrabortty, R., & Hasin, M. (2013). Solving an aggregate production planning problem by using multi-objective genetic algorithm (MOGA) approach. International Journal of Industrial Engineering Computations, 4(1), 1-12.
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