Production planning and control is of great importance for the competitive position of companies and is about managing the flow of materials and goods as well as capacity utilization. An important problem area of production planning and control systems concerns the scheduling and capacity planning decisions. Recently Small-Medium-Businesses face several challenges with their production scheduling. Increased complexity in production layouts and product variety can have an impact on manufacturing service performance measures. One company that must deal with increasing variability in order flow, product variety and complexity in production layouts is BaseClear, a service provider in the field of DNA analysis. BaseClear can be typed as a Small-Medium-Business general flow shop in the MTO industry. BaseClear encounters an unbalanced workload regarding its NGS production department which results in variable Work-In- Process and excessive lead-times. The goal of this thesis is to find possible solutions for this business problem. An answer to the following research question is formulated: How should BaseClear improve the production planning and control of its NGS department to achieve overall balanced Work-in-Process and reduced lead times? The operational performance of the production planning and control of the core-business process of BaseClear, Next-Generation-Sequencing (NGS), is analysed and possible improvements for decisionmaking support based on production planning and control theory proposed to balance Work-In- Process and reduce lead times. After a thorough operational performance analysis structural exceeding lead times and unbalanced Work-In-Process have been determined for the NGS production process. About 10% of all orders have been delivered late in 2016 in comparison to customer agreements and there is variation visible in lead times. Work-In-Process is equally distributed over the NGS production process and waiting time contributes to 67% - 80% of the total lead time on average in 2016. A general finding for all NGS process flows is that sample arrivals are unequally and randomly distributed over the year. No pattern between increasing sample arrival and exceeding lead times could be determined. Lead times are randomly distributed over the year, but in general the variability in sample arrival has an impact on the stability of the production process performance. In 2016 production scheduling is based on the actual sample arrivals and needed data output per period. These two figures determine the number of process steps that are scheduled and performed each week. No impact of sequencing capacity on lead time and Work-In-Process could be distinguished. The sequencing capacity is not limited and no after-ebony effect on lead time is observed. After theoretical and empirical research, it can be concluded that there is overlap with the factors found in practice and the dominant factors found in literature on medium term production planning and control level. Poor insight in operational performance corresponds to the need of capacity control measures and possibility of backlog of work in the shop. Limited capacity equipment, personnel and space corresponds to the need for controlled capacity utilization, workforce availability and flexibility. Lack of a standardized ERP with feedback relates to the need for a capacity planning method. A complex production layout with custom services and high variability relates to type of work content and processing time variation. And finally, variable workload with high peaks and poor insight in customer enquiries for medium-term planning, relates to order arrival variability. After a literature review it has been determined that a balanced order arrival and controlled capacity planning and utilization helps to ensure Work-In-Process balancing and the ability to control and reduce lead times. Total workload must be controlled and should not exceed pre-set maximum limits and a workload input/output control method is needed to manage lead times. It is concluded that 3 workload control in combination with COBACABANA are suitable production planning and control concepts for the high-variety and variable context like in the case company BaseClear. Lead time allowance can be divided into an allowance for the pre-shop pool waiting time and an allowance for the shop floor throughput time. Based on empirical research, guided by a simulation study, the effect of a better-balanced order arrival and an increased number of production batches until the sequencing step is evaluated. The following solutions are proposed that can possibly contribute to accomplish the business goal:  Decrease order arrival variability by realising a constant sample arrival rate.  Increase production batch scheduling from order registration until the sequencing step. Based on theoretical research, the proposed solutions can be made effective in practise by:  Improving the customer enquiry stage (order acceptance/job entry stage) to control the input of work to the job pool.  Determine optimal and maximum levels of WIP for the job pool and shop floor.  Implementation of a dynamic visual workload input/output decision capacity control method, like COBACABANA, by introducing a centralised planning board for an overview of the current workload situation in the job pool and the shop floor, can help to control order arrival and to maintain a minimal workload level in the shop. The number of cards should be set equal to 100% of the workload norm and the number of cards in circulation should be controlled.  Determine optimal release frequencies for the work orders to keep Work-In-Process at the predetermined level in the shop.  Introduction of the anticipated new lower level NGS service with longer promised lead times can help to stabilize the workload of the job pool and the shop.  Introduction of centralized order release control at the job release stage as the main control point can simplify the remaining planning and control process.  Implementation of a standard production schedule with increased number of batches until the sequencing step.  Sequencing run scheduling based on capacity utilization and due dates expiration measures for lowest operational costs.

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hdl.handle.net/2105/41287
Operational Excellence in Services and Supply Chains
RSM: Parttime Master Bedrijfskunde

Getting in control of workload: Analysing and redesigning a production planning and control system of a Make-to-Order general flow-shop for potential improvements guided by simulation. (2017, June 30). Getting in control of workload: Analysing and redesigning a production planning and control system of a Make-to-Order general flow-shop for potential improvements guided by simulation. Operational Excellence in Services and Supply Chains. Retrieved from http://hdl.handle.net/2105/41287