TOC Approach vs Finite Capacity Scheduling for High-Mix, Low-Volume Production
Prasad Velaga, PhD
Scheduling Specialist for High-Variety, Order-Driven Production and Resource-Constrained Projects
The approach of TOC to production management is to find or determine a capacity constraint in the system, ensure adequate subordination to the constraint, do buffer management and exploit the constraint. This is known as Drum-Buffer-Rope (DBR) Method. It is supposed to be a very simple, easy and effective approach for efficiently managing even complex production.
Most job shops which are engaged in high-variety, make-to-order production regularly face a lot of difficulty with production management. Being small in size and revenue, they usually look for simple, low-cost and effective solutions for managing their complex production. Therefore, DBR method is supposed to be ideal for such job shops. However, with some exceptions, those job shops have been avoiding DBR method since the method was developed in early 1980s. Most job shops still generate production schedules using solutions available to them and use the schedules for guidance in controlling and managing production. They implement this approach even if the schedules generated are not of good quality.
The general lack of interest among job shops to adopt DBR method for production management is probably due to the difficulties with subordination and buffer management. Many small and mid-sized industries may not be able to achieve adequate subordination easily and economically in order to adopt DBR method effectively. Buffer management may even resemble firefighting in real time in some industries.
The purpose of DBR method is basically to keep the constraint busy always while controlling work in process in the system. I propose here a more effective method to achieve the same purpose.
Scheduling Approach Based on Proper Finite Capacity Scheduling Logic
Subordination to the constraint is a difficult step in TOC approach to managing complex production. We must do our best to ensure subordination as much as possible. But, there is no guarantee that we can achieve adequate subordination easily and economically.
Generate a detailed production schedule based on appropriate, powerful, finite capacity scheduling logic. If the constraint has any idle times in the schedule, Gantt chart of resource schedules will show those idle times. However, it is very likely that a schedule generated by powerful scheduling logic keeps the constraint busy always (during its available time). The schedule shown at the top of this page is of this type.
If the constraint still remains idle for some time intervals without work as per the schedule as shown in Figure 1, it means jobs are not reaching the constraint in time. This is due to material delays and/or bottlenecks in the system. By analyzing the schedule, we can easily find the reasons why jobs are not reaching the constraint. Proper actions can be proactively taken to prevent such delays and keep the constraint busy.
By generating optimal schedules (using powerful scheduling logic), analyzing the schedule through Gantt chart and taking proactive measures to ensure that jobs reach the constraint in time, we can keep the constraint busy throughout its available time.
Truly powerful scheduling software enables production people to easily implement this method which will be far more convenient, easier and proactive than real-time buffer management in DBR method. I can demonstrate this method to anybody who is skeptical about our method which involves generation and simple analysis of production schedules.
It is needless to say that the utilization of the constraint must be very efficient while the constraint idle time is avoided.
A simple example is illustrated here to convey the intended message. But, production is not so simple in most job shops in real world. Production people can quickly gain a lot of knowledge about the nature of their production by studying Gantt charts of both job shop schedules and resource schedules generated by proper scheduling logic.
The author, Dr. Prasad Velaga of Optisol, LLC has 20 years of experience in developing powerful, scientific scheduling solutions which are regularly used by many complex, order-driven, high-variety production systems.
Lean Construction Shepherd, Author, Kidney Transplant Survivor, TedX Speaker, Graduate Student and Adjunct Professor at Clemson University
2 年Jeremy Moore You have to meet Prasad Velaga!! I'd love to get your perspective on FCS and the amazing things that Prasad and team are doing!
Principal Program Manager at IFS
3 年Prasad Velaga probably I m asking the most basic question. Lets take an example. I m the planner of a job shop where metal fabrication is core business. Lets say I have 10 lathes 3 CNCs, 3 paint booths, 10 drills, 4 welding plants, 6 electroplating baths. lets say I have a product portfolio of 200 different brackets, rods, screws, hooks, ect.. All my machines are finite. paint booth can run multiple operations together from different shop orders. When I schedule my production orders, as late as possible ( ALAP), my software will give me a finite schedule without overloading any of my machine. When creating this finite schedule I can define my target optimization goals.. Things like number of unscheduled orders should be 5%, number of tardy ( late ) orders should not be more than 10%, earliness in days should be less than 20 % of the time horizon. Lets say , my finite scheduler created a schedule satisfying my conditions. (Q1). Observing the schedule provided by my FCS software how do I understand the constraint ? (Q2), is my approach completely against the TOC principles? then what should be the steps. (Q3).Even without defining my optimization goals, with the schedule provided by my FCS software , how to identify the constraint ? - Thank you and your article is very interesting.
Critical Thinker | Problem Solver | TOC Mentor | Consultant.
4 年Hi Prasad, Thanks for sharing the article. Very good content. Just some comments below. Actually, the true goal of the DBR is not to keep the constraint busy, it is to align the capacity to the real demand in the best possible way considering the constraints in the system.? I agree with you when you mention it is difficult to synchronize the resources over the shop floor according the drummer schedule, especially in a complex process. But this is true to any other fine scheduling algorithm that you will put in place in the factory. Actually, the other ones are much harder than DBR because they do not have inherent tools to handle with variability as the DBR has. Using right buffers in the right places you will minimize the impact of unplanned variability, which is just possible in fine scheduling with huge efforts of constant re-planning.? The solution of TOC to simplify the planning and controlling processes is the same of other algorithms. Use software to minimize the manual work of calculation and distribution of the scheduling over the resources. We are using 1Beat (https://1beat.com) solution in our manufacturing projects with a very high level of success all over the world.? Most scheduling tools using Gantt charts to visualize the load level per resource, and I personally think this is very good. But this don’t make your life easier when the constraint is constantly changing according the products mix or due to unplanned breakdowns. In real life, most part of the times, the real constraint is not internal, and the company has capacity enough to attend the market demand. In those cases, I prefer to use sDBR to simplify the implementation and achieve results faster. Regards, Ricardo Leite
Scheduling Specialist for High-Variety, Order-Driven Production and Resource-Constrained Projects
4 年While defending my FCS method, I have written the following in some other thread. I did not reveal how the uncontrollable natural variation is accounted in my specific FCS implementation. To accommodate it, I would schedule material release (early enough) such that jobs have some waiting times before the constraint. Those waiting times are expected to address the impact of variability. For a few more details, please read our web page, https://optisol.biz/lean-production/ . I see two components of variation in job shop production: (1) high known variation in process requirements of jobs and (2) uncontrollable natural variation in the system. My method distinguishes both components of variation and finds material release time for each order accordingly. In my method, the buffer size is determined on the basis of the second component of variation. You would not see buffer sizes in typical FCS implementation. The idea behind the analysis of variance (ANOVA) method in statistics is that decision-making will be more accurate when we separate the effect of large deterministic factors from that of error (natural variation) in the total effect. I have not seen this notion in TOC for manufacturing.
I help logical leaders improve profitability and create long term change. Ask me how :) Want to talk? Schedule a time at calendly.com/kevinkohls or go to linktr.ee/kevinkohls
4 年Drum Buffer Rope is a bit old in the tooth now. I would spend time looking at #DDMRP for how pull signals are generated for job shops and distributions. It's based on TOC and Lean concepts. The key aspect with both DBR and DDMRP is the acceptance of Variability and Dependence, something most scheduling systems do not accord for.