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Measuring and Managing Capacity Costs
Published in C.J. McNair, Richard Vangermeersch, Total Capacity Management, 2020
C. J. McNair, Richard Vangermeersch
Having established the baseline capacity of a process, the focus of the capacity cost management system design shifts to measuring the deployment of the capacity deemed to be available for use. There are generally believed to be five major categories of capacity deployment:6 productive capacity, planned idle capacity, unplanned nonproductive capacity, excess capacity, and nonproductive capacity. Productive capacity is capacity that provides value to the customer. Productive capacity is used to actually produce a product or provide a service. According to existing MAAP, the estimated cost of a unit of productive capacity should be based on the theoretical, assumed, maximum value-creating ability of the firm.7Planned idle capacity is nonproductive capacity that is currently not scheduled for use, having been set aside due to temporary lack of demand, preventive maintenance, or other management policy-driven reasons, such as planned shutdowns. Unplanned nonproductive capacity or unplanned idle time, on the other hand, is capacity planned for use that is temporarily out of action due to process variability, such as the lack of materials, machine or process breakdowns, or other delays or process defects.
Making the Best Use of Your ERP System
Published in Timothy McLean, On Time, In Full, 2017
At the core of the problem is the use of material requirements planning (MRP), which is one part of the ERP system. What the MRP does is calculate your requirements for finished goods, work in progress, and materials. It essentially tells you what to make, when to make it, what materials to order, and when to order them. To do this, it uses a forecast (remember Chapter 3). The ERP contains a big table of business rules and data called the master production schedule (MPS). This includes things like lead times for key processes and supplies, safety stock levels, optimum production and order quantities, and rules about how and when to schedule production. With advanced planning and optimization systems, this will go all the way down to scheduling the sequence of work on individual work centers and doing “finite scheduling” where demand is allocated to manage production capacity.
The Lean Way of Doing Business
Published in MJS Bindra, Ekroop Kaur, The Lean Business Guidebook, 2022
Once the value streams have been identified, the next step is to ensure a smooth flow of each activity in the value stream. This requires removal of obstacles and bottleneck processes so that the time taken in the value stream is as low as possible. The bottleneck process is that process in the value stream that has minimum production capacity per hour and determines the output rate of the value stream. The bottleneck processes can be like waiting for decisions, review of work done or queuing of material from a faster process. The bottlenecks should be scrutinized to identify the issues so that corrective action can be taken to increase the output.
A joint production-workforce-delivery stochastic planning problem for perishable items
Published in International Journal of Production Research, 2022
Pedram Farghadani-Chaharsooghi, Pooria Kamranfar, Mohammad Seyed Mirzapour Al-e-Hashem, Yacine Rekik
In future studies, one could consider greenhouse gas emissions and extend the proposed solution by adding a second objective function to the model called the reduction of the supply chain CO2 footprint. Besides, the hiring and firing costs are considered constant in this study, while the hiring cost of each worker can be viewed as a variable. The time required to familiarise the worker with the environment is neglected, which can be added to the model by converting it into a currency unit. The cost of firing any worker might impact the brand validity and credibility, in addition to administrative costs, which is not modelled in this study. Besides, one possible future research direction is to consider having a limited number of candidates to be hired at the beginning of the planning horizon. So, the production capacity is determined by both equipment and the number of workforces.
Managing uncertainty in demand through inventory and workforce development
Published in International Journal of Production Research, 2021
Silviya Valeva, Mike Hewitt, Barrett W. Thomas
While the testing environment was kept simple enough to allow us to derive general and widely applicable insights, a manufacturer may face different constraints or make decisions based on a different objective. Thus, seeking to validate and generalise the managerial insights pertaining to capacity and inventory development, further research can study different production settings. For example, hiring and attrition could have a significant impact on capacity as new workers generally have low initial productivity and reductions in workforce can disrupt production capacity. Additionally, other sources of learning could be considered, such as formal training, transfer of knowledge between team members in the workforce, and forgetting due to fatigue or periods of time away from the job. Similarly, shared tasks between production lines could provide an additional source of learning, so that experience between product tasks is transferable. Furthermore, capacity constraints on inventory levels (e.g. the extreme case of no inventory allowed) and/or different objectives (e.g. minimising lost sales) as briefly explored in the Appendix, could also be significant in determining optimal scheduling decisions and cross training patterns. Finally, the solution approach currently looks ahead only one period. Future work could explore methods for both overcoming the action space and looking to the end of the horizon.
Toward sustainable electricity generation mix: an econometric analysis of the substitutability of nuclear energy and hydropower for fossil fuels in Canada
Published in International Journal of Green Energy, 2021
Sakiru Adebola Solarin, Mufutau Opeyemi Bello, Olabode Eric Olabisi
The foregoing results suggest that both nuclear energy and hydropower have positive effects on economic growth and being able to substitute coal and natural gas in Canada. The results can be attributed to several reasons. The foregoing results can be justified on the basis that an increase in investment has accompanied the deployment of nuclear energy and hydropower in Canada. Hydroelectricity infrastructure attracted investments running into several billions of dollars in Canada in 2013 (Canadian Hydropower Association 2015). The government in Canada has committed more than a billion worth of investments to renovate its Chalk River Laboratories (CRL) through the refurbishments of vital nuclear site facilities including new and world-class science infrastructures (Canadian Nuclear Association 2019). Investments in new technology increase productivity and the productive capacity of the economy, which assists to shift the long-run aggregate supply to the right. An increase in long-run aggregate supply is essential for long-term economic growth. Investment leads to a substantial rise in productivity as well as an increase in the productive capacity of the country.