The use of optimization techniques for managerial decision-making is popular. Various tools have been developed to help fit few resources to production processes with the aim of maximizing profits and reducing wastage of resources. This paper looks into this aspect with a special interest in simulation.
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Simulation is a technique that tries to replicate a real life scenario into a model. With reference to case study examples, this paper analyses methodologies adopted in applying this technique in product planning and scheduling. The researcher also reviews literature in this field to get greater insight into the topic. The paper concludes that simulation is a critical tool for business success as long as it is installed after careful preparation and steps taken to ensure it reflects the needs and objectives of the organization.
Simulation is a manufacturing technique that aptly represents reality of operations and processes in a model. The model is a reflection of what happens in reality and takes into account the parameters and conditions on the ground. It is quite a useful tool in product planning and scheduling. Scheduling is the act performed by managers where they allocate resources, indentify procedures, and estimate different parameters that entail the procedures, such as costs.
This is quite imperative in project management as it informs the project manager about the imminent project and acts as a tool for prediction. Product planning, on the other hand, refers to the process of allocation of meager resources to production activities with the aim of ensuring that company objectives are met.
This includes customer satisfaction and meeting demand. Generally, this represents an optimization problem for a company as it refers to a process where a manager has to make a decision to minimize costs and maximize profits simultaneously. This paper looks into the possibility of applying simulation to solving production planning and scheduling problems in different organizations.
The researcher employs the use of case studies and previous applications of these tools to reflect the advantages, disadvantages, problems, and possible solutions inherent to the usage of simulation in these functions. Through evaluation of this case study, the researcher points out recommendations of the issues that manufacturers encounter in using this powerful function (Chase, Jacobs & Aquilano, 2006).
This section looks into the literature surrounding the use and application of simulation in scheduling and production planning. The review points out the disadvantages and looks into the possibility of improper application of this tool in different companies.
Production planning refers to the act of striving to meet market demands through effective and efficient usage and application of resources in a manufacturing or service firm. Production planning, according to Graves (1999) is quite an effective tool in reaching optimal solutions to managerial problems.
It is applicable to staff planning, how many lots to produce in a particular time, how to allow extra work time, and how to sequence production runs effectively. Since this is an optimization problem, different tools can be used to solve them. This is informed by the nature of the manufacturing, the level of technology and size of the organization in question. Examples of optimization solution techniques are linear programming, simulation, and complex computer software (Chase, Jacobs & Aquilano, 2006).
Graves (1999) also points out that to use a certain technique certain features about the product and production processes must be accounted for; for instance, the time of production. This informs the usage of certain techniques. The use of simulation is quite popular. This is because of the possibility of putting the model on a test run and coming up with the model that fits the organization perfectly (Chase, Jacobs & Aquilano, 2006).
In certain situations, it is relatively easier to use compared to others. Additionally, the possibility of putting these models on a test run effectively makes it quite flexible and admirable. In production planning, according to Graves (1999), this technique is the most widely spread. An organization needs to indentify certain objectives and come up with a list of the constraints or limitations or resources. This is put into a model that replicates the actual situation on the ground.
Another way to solve production-planning problems that is widely applicable in many organizations is linear programming. It is almost similar to simulation but it has the limitation of many assumptions. Hence, it may not reflect the reality on the ground as noted by Graves (1999).
During the development of a project, it is imperative to ensure that activities that lead to the completion of the project are commenced appropriately and their deadlines met. Deadline represents one of the constraints of a project. Others include the scope of the project, the cost or budget allocated, goals, and objectives set out in the project (Chase, Jacobs & Aquilano, 2006).
In a manufacturing set-up, operations scheduling entails dispatching, controlling, tracking, and monitoring of production in the shop floor. It is imperative to ensure that certain functions within a manufacturing plant run smoothly.
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For example, scheduling is highly applicable to personnel allocations to work centers, equipment allocation, capacity planning, prioritization, and determination of order performance. Additionally, scheduling helps managers to control activities at the shop floor so that orders with relative urgency are dispatched (Chase, Jacobs & Aquilano, 2006).
Hence, this is a very important function in ensuring smooth operations of a manufacturing plant. It is also quite important in the overall success of a company as it directly affects the demand.
Figure 1: Typical Scheduling Process
Figure 1 above represents a typical scheduling process where controls are carried out by software. The software maybe designed from a simulation run by the firm over a long period. It captures activities in the whole process with necessary parameters. It details each person’s requirement in the process (Chase, Jacobs & Aquilano, 2006).
Scheduling is quite important as it plays a huge role in minimizing idle time from machines and personnel, reduces time spent by a product before it is finally released in market, and helps in meeting deadlines in the downstream of a market.
Application of Simulation in Scheduling
Companies apply production planning using a top-down approach that goes to finer details (e.g. from days to hours). Essentially, the management allocates real orders to the available resources to meet maximal capacity utilization, minimize work in progress, reduce chances for delays, and to have as minimal thorough-put times as possible. It is important to note that these needs are frequently in conflict.
Depending on the needs of an organization, different methods may be used, for example assignment techniques, simulation techniques and computer software. Since this paper looks into simulation, it is crucial to note that it is applied in two levels. First, a simulations model may be developed that tests and configures an existing tool of planning. Hence, it is just a fine tuning tool and is not part of the production process.
Secondly, simulation may play a direct role in production if it is installed in the system. In this case, it is referred to as an Advanced Planning and Scheduling (APS) tool. Essentially, it does most of the functions captured that define scheduling such as allocating tasks, equipment, and order processing and updates on Work in Progress (WIP).
The use of these systems does not mean that organizations or companies gain from their applications. The case study highlights areas where many companies may end up confused by the whole system. Data stored in these systems, especially the APS, may reveal many anomalies. This is partly because of lack of proper reflection. For example, a German toy manufacturer in the case study had the following anomalies.
|Anomaly||Degree of anomaly|
|Work stations||Less that 50% of work stations (140 in total) were in use|
|Capacity||Some work stations had zero capacity utilization while others had over 500% utilization|
|Synchronization||Lack of synchronization between shop floor reality and system reflection|
Figure 2: Anomalies in System
Findings and Suggested Solutions
A company (Decopart) that supplies aluminum parts used the APS system quite effectively. The management employed the use of experts to carry out the technical work. Additionally, Decopart uses up to date tools for this processes, which are easily adaptable to the changes in production or market demand. They have the capacity to detect the need for more resources and any delays or idle times. It is also quite integrative which means it reflects the whole organization is functioning.
The system took quite some time to install. This ensured that the company came up with many processes that were in contrast with the objectives of the systems. Additionally, through use of a model, the company was able to fine-tune the system to reflect its future capacity requirements. Hence, it is imperative to understand your organization well before installing this system (Mapes, Szwejczewski & New, 2000).
Advantages and Disadvantages
Simulation has many advantages. First, it allows a company to study the whole organization as a model before installing the model to its operations. This is an important step as it brings out the bottlenecks that the company should deal with in future. Additionally, it allows the company to adjust to the needs of the organization and to the system with the aim of achieving certain goals.
Depending on how well it is used, how well it is designed, and the level of preparation before the full installation, a company is in a position to adjust positively to any changes that may occur in future affecting the system. This includes the need for more resources, changes in market demand, creation of new workstations, and changes in personnel duties (Mapes, Szwejczewski & New, 2000).
The system is quite costly to roll out. Decopart used quite a huge sum of money to set up its own system. Although it effectively, connects major manufacturing functions in an organization, care must be taken in training. This is because many employees may find it tiring to adjust to the needs of the system and hence affect its functions. Additionally, enough expertise must be sought to put the relevant data captured in the system to good use. This is because, it is inappropriate to have all that information without aiding in managerial decisions.
Application of Simulation in Production Planning
In a production process whose steps are predefined, application of simulation is quite possible. For example, the case study presents a company that produces prefabricated concrete parts for houses. Certain steps are performed in certain duration using predetermined times. Machines are programmed to know cycle times and locations of a part during production. Hence, it forms a continuous process.
This is after a careful analysis of previous production using a simulation model. The model can tell how many products are likely to be produced with defects and can be tweaked to ensure that these defects are reduced to the minimum and detected before the product reaches the customer. The company uses an online simulation, which records sales data and uses this data to reflect what to produce (Mapes, Szwejczewski & New, 2000).
Creating such a system requires quite a lot of time. Previous operations should be captured and appropriate software created to reflect this information. For example, the case has a company that was in the business of painting cars. More than 100 colors were in use and certain procedures in the painting process resulted in delays, long transitional times, and idle time. This contributed to a challenge in trying to come up with an appropriate model. Hence, some business functions may be difficult to put into a simulation model (Krauth, 2010).
Advantages and Disadvantages
As noted above, not all process can be put into a model. Some are a bit complex and hard to simulate. The use of ISSOP optimization tool helps in these situations. It has an inbuilt tool that caters for many aspects of production such as production planning, throughput times, idle times, and capacity.
However, a slight tweak in the system may cause considerable danger to the production process and steps must be taken to ensure that there are corrective measures in place. Additionally, simulation software requires a human interface. Although some are quite automated, some defects can affect a huge roll out in production leading to catastrophic consequences (Krauth, 2010).
Evaluation of the Case Study
The case study was a critical look at the optimization and simulation tools in place in major organizations and SMEs. The case presents a number of small businesses that are using these tools in production planning and scheduling. It also highlights the challenges, advantages, and appropriate software for the different organizations with specific needs.
It also looks at the suitability of these models for the future and critically analyses the level of applicability: is it a support system or the main system? The case also looks into the issue where some problems cannot be captured in a system and their effect on the overall need to meet certain objectives. For example, personnel morale is an independent variable whose effect may not be captured in the system. Offline and online simulation and their respective advantages are also discussed in detail (Krauth, 2010).
Summary of Findings and Recommendations
The case’s major finding is that although many companies use simulation and optimization systems, majority are not satisfied with them. It is hard to understand the system as a nonprofessional and appropriate training and preparation are crucial to the success of such production planning and scheduling systems.
Additionally, it is important to note that much software has been developed to analyze the functions of a system but specific companies that should insist on that specific software which appropriately captures the needs of the company. Certain decisions can be made directly using software solutions (Krauth, 2010). For example, it can allocate responsibility to personnel, detect idle time, and reflect urgent demands. However, it cannot capture the mood of personnel and this may lead to ‘invisible causes of bottlenecks’.
Hence, it is crucial for the management to continuously asses every aspect of an organization with the aim of reducing and capturing such bottlenecks. As the company, Decopart found out, a production process, which has many available options, reduces the effectiveness of creating a simulation or optimization system. Hence, much time needs to be dedicated to such processes to reduce chances of a defective system (Krauth, 2010).
Many companies employ optimization and simulation techniques to solve managerial problems. These solutions are meant to enhance decision-making capability of the management. The case looks into the use of simulation in particular towards finding solutions in product planning and scheduling functions of an organization. The case study presents a number of companies whose optimization software solutions, as a direct business function or as an assisting function, helps in streamlining operations.
For instance, a car painting business that uses simulation software to run its operations with tremendous results. It is crucial to note that the optimization and simulation solutions are not entirely good for all organizations. Certain steps need to be carried out to ensure that the solutions are successful. For instance, ample preparation, knowing the market, personnel training, and motivation packages are crucial steps. Additionally, proper expertise is a fundamental requirement towards realizing this goal (Krauth, 2010).
Chase, B.R., Jacobs, R.F. & Aquilano, N.J. (2006). Operations Management for Competitive Advantage. New York: McGraw Irwin.
Graves, C.S. (1999). Manufacturing Planning and Control. Web.
Krauth, J. (2010). Simulation Supports Production Planning and Scheduling. Berlin: Sim Serv.
Mapes, J., Szwejczewski, M. & New, C. (2000). Process Variability and Its Effect on Plant Performance. International Journal of Operations and Production Management, 20 (7): 792-808.