What was missing in the MRP for the APS to emerge
Many people ask us what APS software is, what it does and what kind of demand it is relevant. So in this article we will talk a little more about how the APS software and the main gaps in the MRP and ERP systems that it supply.
The origin
Production planning, in its broader concept, has always been in the heart of industry. It may be that in recent decades it has not been treated with the consideration due to other areas, but it has the role of protagonist in the history of technology for management in the industry. In the 1950s, computational development has introduced the computer-aid design, but its high cost made it accessible for a few, in case the aerospace and automotive industries, which have) very high technical demand. But the management was still "in the arm". The growing economic expansion, along with industrial development, has made planning challenges more critical. Thus, the first business systems initiative for the industry was neither a financial nor commercial system, but it was MRP (Material Requirements Planning), created in the 1960s by Oliver Wight and Joseph Orlicicky, precisely to plan materials to manufacture and buy.
For you who arrived with the tram walking, basically MRP generates net needs of these materials from the needs of finished products and their explosion through the different levels of a product structure, generating the needs of each material at each level, whether an intermediate component produced internally or a purchased raw material. Each of these needs has a date stipulated through leading resupply standard teams for each item. MRP is nothing more than a series of simple and chained calculations, but in industries that have many components and structure levels this is a hand on the wheel, especially if we look at the time when it has arisen. How innovation loves problems, the growth in demand for industrialized products after the 1960s bumped into the next planning challenge: capacity. It was no use just knowing which materials would be needed in each period, but also if it would be possible to produce or buy the indicated volume, as well as see the financial impacts. In it, resource management was considered, with interface with financial and engineering areas to understand physical and financial needs of labor, machinery and materials for the execution of a production plan.
From the MRPII the Master Plan Schedule Production Plan is defined, which is the definition of finished products to be produced in a period (already disaggled by SKU). Therefore, knowing what we will need finished products and understanding, roughly, that it is possible to produce, explode the needs of all materials through the well-known MRP. Finally, all the needs generated by the MRP are validated. It travels all operations recorded in the product manufacturing script and consumes the times to produce those full capacity products of each productive center. On the basis, it is what many know and practice as a machine load in industries. These concepts all were not ready with the birth of MRPII. They have been improving over time. The growing industrial demand and this technological evolution spreading in several needy areas have provided that in mid -1990s, integrated management systems or only ERP (Enterprise Resources Planning) emerge. These integrate the different areas of a company: accounting, human resources, financial, engineering, manufacturing, commercial, among others. ERPs emerged seeking to incorporate one or more of the functions we described earlier. The limitations of existing systems so far for production programming to be performed in an assertive manner encouraged the creation in the same decade of the finite programming (FCS - Finite Capacity Scheduuling), which later evolved to advanced planning and programming (APS) Scheduling). It is vital to understand that both emerged to supply the deficiency of other systems in managing a finite production capacity, as well as managing queues, routes and synchronism between production operations. Let's explore these limitations
:Fixed Lead Time
Probably you, as well as the vast majority of people in the world, get around home daily to your work. Although you have a time in mind of how long it is normally the route, if you monitor this time daily, you will notice that there is a significant variation, especially if you live in a large city. This time can be even more oscillating there is a work or event on some street in your way that makes it vary the way. So a factory is a megalopolis that has more or less congested routes every day. For you, leaving 10 minutes earlier to ensure that it will arrive on time can cost little. However, for an industry, these "10 minutes" on the scale of hundreds or thousands of production orders, deadlines and resources generates a very costly error from a planning point of view. Both MRP and MRPII use fixed lead teams, ie they do not see that their path to work changes duration if you change your route or if the roads are bottled. The more operations per product, the more resource alternatives or itineraries, and the higher the demand variation over time, the greater this divergence. The direct consequence is the difficulty that industries have in determining delivery deadlines and ensuring inventory at a healthy level. No wonder most companies are still supported by these systems and, not coincidentally, make up a growing volume of industries that complain about delays, ruptures and spare problems.
Batch or batch processes
Another point of attention is batch or batch processes, such as thermal treatments, painting booths, galvanization, dyeing, wear outlaws, among other types of operations that process multiple products simultaneously. MRP and MRPII do not distinguish these processes from those that are defined through a time by item (or weight, or length) or rate per hour. Thus, the load of these processes is poorly sized and the defined production plan will be less likely to be performed properly. Some claim that these processes are not a bottleneck in their industries always. This tends to occur in the thermal treatments of metal-mechanical industries, but in virtually all other cases these processes have a strong tendency to become bottlenecks quite often. In addition, based on a few hundred industries we have visited in many years, we can say that approximately half of them have this type of process, thus having this problem.
Synchronism
When we have cases where there is more than one operation to transform a product, there is naturally a sequence to follow between them. There is no way to pack the product before painting or assembling. The manufacturing script is the reference for this order between the activities. But the CRP cannot handle this aspect of synchronism. Usually this is treated in two ways. At first, it carries all operations in the same capacity period. However, depending on the line that is formed in each process, a later process should be allocated in the next period and its expected delivery date should be changed and what happens is the delay of this production order. In other cases, especially when process times are longer or there are many operations, it is defined that a set of operations will be in period 1, while another will be in period 2, and so on. A sequential logic in time is created, which is good, but the usual consequence of this scaling turns out to be a great dilution of production. Total lead teams increase, the real value aggregation time on this total becomes low, and the stock in the process consequently also rises. This second scenario tends to generate less delays, but at the expense of system -created inefficiency.
Finite capacity and restrictions
Perhaps this is the main factor that makes the result of MRP just a feedback of a test that cannot be required minimum grade because it is not known if it will be possible to solve it. Defining what you should produce or buy without validating capacity in theory would not allow us to charge results consistent with the factory. Usually there is not only one bucket with a capacity that is filled either: it is not just a machine or a job that restricts capacity. People who operate the machines, the tools used, the physical space between sectors and various other criteria are usually restrictive. A specific capacity analysis for the main restriction of each process or, worse than that, just for the bottleneck, is very limited. Now, if we join this finite capacity factor with its restrictions on what we talk earlier - the synchronism - we will see that the hole is below. It is no use making a machine load to limit capacity if we do not see that that product, which is apparently promised to be produced and delivered, can no longer be processed because today an indispensable tool for its production is being used in another machine. This kind of situation, involving tools and labor, is more frequent than you think.
The sequence
If we analyze the 7 losses of Lean Manufacturing brought by Taiichi Ohno, we see that two of them are directly related to production sequencing: the waiting and processing losses, through the setups. There are processes that your setup times can reach 50% of the total time available in certain periods. Ask experts how long to change a loom cylinder or to wash a tank before producing allergenic foods. Depending on the sequence of operations you set for each feature, you can significantly reduce mold and tool adjustment times, tann and pipe cleaning, color hits and even operators handling. Since these systems (MRPII/CRP) do not consider the sequence of operations, they tend to use averages of setup time, contained, they can vary between 5 minutes and 3 hours, and use an average will likely cause problems in the ending estimates of a process. Since there is usually more than one operation to produce something, this error that may seem small, it is reflected in later processes and a domino effect occurs, misunderstanding initial planning. In the same line of thought, if we do not say a sequence, a shift can produce a certain production and leave it to the next shift products that cannot be processed by it as there is no team to perform the Setup in that specific shift, or it is a product that needs more machine operators and in this shift there are no enough people, among other possible factors. This will generate more waiting times between processes, the other loss of OHNO. Finally, in practice we see that systems that ignore important factors to be assertive incite a vicious cycle of empirical goals and controls full of simplifications that make it difficult to connect actions and results. To eliminate these gaps pointed out, it is necessary to work with a more advanced method and technology. Behold, the APS emerges.
But APS means Advanced Planning and Scheduling, ie it is software for advanced production planning programming. APS is an expert system, its idea is not to replace the ERP, but to complement and meet its gaps, working on it, processing production and sequencing information, taking into account all restrictions, finite production capacity and the necessary synchronization, thus showing the best way to perform production according to each company's strategies. Neo is the largest APS consultancy in Latin America. Realize the sequencing of its production with those who specialize in technological solutions.