What the MRP lacked for the APS to emerge
Many people ask us what APS software is, what it does and what kind of demand it is relevant for. So in this article we're going to talk a bit more about how APS software came about and the main gaps in MRP and ERP systems that it fills.
THEORIGIN
Production planning, in its broadest sense, has always been at the heart of industry. In the 1950s, computer development introduced CAD (Computer-Aided Design) to engineering, but its high cost made it accessible to only a few, in this case the aerospace and automotive industries, which had (and have) very high technical demands. However, management was still "by hand". Growing economic expansion, together with industrial development, meant that planning challenges became more critical. Thus, the first business systems initiative for industry was not a financial or commercial system, but MRP (Material Requirements Planning), created in the 1960s by Oliver Wight and Joseph Orlicky, precisely to plan the needs for materials to be manufactured and purchased.
For those of you who are just getting started, MRP basically generates net requirements for these materials from the requirements for finished products and their explosion through the different levels of a product structure, generating the requirements for each material at each level, whether it's an intermediate component produced in-house or a raw material purchased. Each of these requirements has a date stipulated through standard resupply lead times for each item. MRP is nothing more than a series of simple, chained calculations, but in industries that have many components and levels of structure, it's a godsend, especially if you look at the era in which it emerged. Because innovation loves problems, the growth in demand for industrialized products after the 1960s ran into the next planning challenge: capacity. It was no good just knowing what materials would be needed in each period, but also whether it would be possible to produce or buy the volume indicated, as well as seeing the financial impacts.Thus, in the 1980s, MRPII was born. In MRPII, resource management came to be considered, interfacing with the financial and engineering areas to understand the physical and financial needs of labor, machinery and materials for the execution of a production plan.
MRPII is used to define the Master Production Schedule (MPS), which is the definition of the finished products to be produced in a given period (already broken down by SKU). Then, knowing what we will need in the way of finished products and understanding, roughly speaking, that it is possible to produce them, we explode the needs for all the materials using what is already known as MRP. Finally, all the requirements generated by MRP are validated. It goes through all the operations recorded in the product's Manufacturing Routing and consumes the times to produce those products from the total capacity of each production center. In essence, this is what many people know and practice as machine loading in industry. All these concepts did not come ready-made with the birth of MRPII. They have been refined over time. Growing industrial demand and this technological evolution spreading into various areas that were still lacking led to the emergence of Integrated Management Systems, or just ERP (Enterprise Resources Planning), in the mid-1990s. These integrate the different areas of a company: accounting, human resources, finance, engineering, manufacturing, sales, among others. ERPs were created to incorporate one or more of the functions described above. The limitations of the systems that had existed up to that point to enable production scheduling to be carried out assertively led to the creation, in the 1990s, of the concept of Finite Capacity Scheduling (FCS), which later evolved into Advanced Planning and Scheduling (APS). It is vital to understand that both emerged to address the shortcomings of other systems in managing finite production capacity, as well as managing queues, routes and synchronization between production operations. Let's explore these limitations
Fixed Lead Time
You, like the vast majority of people in the world, probably commute from home to work every day. Although you may have a rough idea of how long your commute usually is, if you monitor this time on a daily basis, you'll notice that there is a significant variation, especially if you live in a big city. This time can fluctuate even more if there is a construction project or event on a street along your route that causes you to vary your route. So, a factory is a megalopolis that has more or less congested routes every day. For you, leaving 10 minutes early to make sure you arrive on time may not cost much. 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 times, i.e. they don't see that your journey to work changes duration if you change your route or if the roads are jammed. The more operations per product, the more alternative resources or routes, and the greater the variation in demand over time, the greater this divergence will be. The direct consequence is the difficulty industries have in determining delivery times and guaranteeing stocks at a healthy level. It's no wonder that a large number of companies still rely on these systems and, not coincidentally, they make up a growing number of industries that complain about problems with delays, shortages and overstocking.
Batchor Batch Processes
Anotherpoint of attention is batch processes, such as heat treatments, paint booths, galvanizing, dyeing, wear machining, among other different types of operations that process multiple products simultaneously. MRP and MRPII do not distinguish these processes from those that are defined by a time per item (or weight, or length) or rate per hour. As a result, the load on these processes is poorly dimensioned and the defined production plan is less likely to be executed properly. Some claim that these processes are not always bottlenecks in their industries. This tends to be the case with heat treatment in metalworking industries, but in practically all other cases these processes have a strong tendency to become bottlenecks quite often. What's more, based on the hundreds of industries we've visited over many years, we can say that approximately half of them have this type of process, and therefore have this problem.
Synchronization
Whenwe have cases in which there is more than one operation for the transformation of a product, naturally there is a sequence to follow between them. You can't pack the product before painting or assembling it. The Manufacturing Routemap is the reference for this order between activities. But CRP can't cope well with this aspect of synchronization. In the first case, it loads all the operations in the same capacity period. However, depending on the queue that forms in each of the processes, a later process should be allocated to the next period and its expected delivery date should be changed and what happens is that this Production Order is delayed. In other cases, especially when process times are longer or there are many operations, it is defined that one set of operations will be in period 1, while another will be in period 2, and so on. This creates a sequential logic in time, which is good, but the usual consequence of this staggering ends up being a great dilution of production. Total production lead times increase, the time it takes to add real value to this total becomes low and stocks in process consequently also rise. This second scenario tends to generate fewer delays, but at the cost of inefficiency created in the system.
Finite Capacityand Constraints
Perhapsthis is the main factor that makes the MRP result just a template for a test that you can't ask for a passing grade because you don't know if you'll be able to solve it. Defining what should be produced or purchased without validating capacity, in theory, would not allow us to charge the factory for consistent results. Normally there isn't just a bucket with a capacity that fills up either: it's not just a machine or a job that restricts capacity. The people who operate the machines, the tools used, the physical space between sectors and various other criteria are also usually restrictive. A specific capacity analysis for the main constraint of each process or, worse still, only for the bottleneck process, is very limited. Now, if we combine this finite capacity factor and its constraints with what we talked about earlier - synchronism - we can see that the hole is deeper. There's no point in doing a machine load to limit capacity if we can't see that the product, which is apparently promised to be produced and delivered, can no longer be processed because today a tool that is indispensable for its production is being used on another machine. This type of situation, involving tools and labor, is more common than you might think.
ASequence
Ifwe analyze the 7 losses of Lean Manufacturing brought up by Taiichi Ohno, we see that two of them are directly related to production sequencing: waiting and processing losses, the latter through setups. There are processes where setup times can reach 50% of the total time available in certain periods. Ask the experts how long it takes to change a loom cylinder or wash a tank before producing allergenic food. Depending on the sequence of operations you define for each resource, you can significantly reduce mold and tool setting times, tank and pipe cleaning, color matching and even operator movement. As these systems (MRPII/CRP) don't take into account the sequence of operations, they tend to use averages of setup times, which can vary from 5 minutes to 3 hours, and using an average will probably cause problems in estimating the end of a process. As there is usually more than one operation to produce something, this error, which may seem small, is reflected in subsequent processes and a domino effect occurs, de-characterizing the initial planning. In the same vein, if we don't dictate a sequence, a shift can produce a certain output and leave products for the next shift that can't be processed by the same shift because there isn't enough staff to carry out the setup on that particular shift, or it's a product that needs more operators per machine and there aren't enough people on that shift, among other possible factors. This will generate more waiting times between processes, Ohno's other loss. In short, in practice we see that systems that ignore important factors in order to be assertive incite a vicious cycle of empirical targets and controls, full of simplifications that make it difficult to connect actions and results. To eliminate these shortcomings, it is necessary to work with a more advanced method and technology. This is where APS comes in.
Butwhat is APS software anyway? APS stands for advanced planning and scheduling, i.e. software for advanced production planning. APS is a specialist system, the idea of which is not to replace ERP, but to complement and address its shortcomings, working in conjunction with it, processing production and sequencing information, taking into account all the constraints, the finite production capacity and the necessary synchronization, thus showing the best way to carry out production according to each company's strategies. NEO is the largest APS consultancy in Latin America. Sequence your production with a specialist in technological solutions.