The countdown to the Bundestag election is running!

We are conducting a short survey on the subject of production planning. Choose with us!

Dear Ladies and Gentlemen,

the countdown to the Bundestag election is running… at the FLS, too.

We do a short survey about production planning. Vote with us!

Vote until 22 September and let us know which requirements your production planning system should meet:

You will see the results of all participants at the end.

Many greetings

Your FLS Team

FLS News – Seasonal fluctuations in production?

Summer break, not for you! Your production does not stand still. We have the following topics for you in today’s newsletter: Season planning, shelf life and set-up times … optimize and produce more cost-effectively.

Overview of topics

How does your production react to seasonal fluctuations?

Planning system sweetens praline production Hachez user report for download.

Setup time matrices are no longer up to date. Learn how to halve your setup times.

Cut seasonal tips at the push of a button

Automatic seasonal balancing for optimal capacity planning in the food industry. New module equalizes production and eliminates bottlenecks in personnel and materials.

The new module “Seasonal compensation” of the production planning system “Fekor” equalizes seasonal peak loads in food production. It relieves the planner of computing work and reduces the effort for seasonal planning to almost zero. In addition, it plans personnel deployment and material procurement at the same time.

The seasonal business in particular places high demands on the production planners, because the limited shelf life of the products means that they cannot be produced at any early stage.

A concrete example: Milk chocolate has a higher milk content than bitter chocolate. It must not be produced so early that it only has a low residual shelf life when it reaches the trade. A bitter variety with a very low milk and cream content, on the other hand, can be produced weeks earlier.

If the production of products for the seasonal business is preferred, then it must only be those with a minimum shelf life that still meets the needs of the consumer despite the early production.

Previously, planners had to work days or weeks to plan production, personnel deployment and material procurement for the coming season.

The “internal shelf life” counts

The new seasonal compensation module reduces the effort for seasonal planning to almost zero: It works parallel to the day-to-day business of the planner without further burdening him – seasonal planning is automatically created as a by-product of daily or weekly detailed planning.

The “internal shelf life” is added to the minimum shelf life of a product printed on the packaging: It begins as soon as the goods are produced and stored. This value is stored once for each article and is continuously included in routine production planning from that point on. This eliminates the need for separate planning for seasonal business, but production is still optimally utilized at all times.

In addition, the system automatically calculates when the material must be ordered and delivered. This applies not only to the raw materials, but also to the packaging and all other materials required to complete the product.

The automatic seasonal adjustment also calculates when and how many additional employees need to be hired in order to cope with early production. In this way, personnel requirements are precisely predetermined.

Seasonal planning is a module of the “Fekor” production control system, which FLS has developed especially for the food industry with its industry-specific requirements and which has proven itself for years in production planning in the plants of several manufacturers in the food industry.

Screws have no best-before date

Compared to other manufacturing sectors, the food industry must take additional criteria into account during production, which make planning complex. In addition to the limited shelf life of the products and the pronounced seasonal business, sequence planning is also more complex than, for example, in mechanical engineering – for example, when it has to be ensured that different products do not mix.

Stefan Bastian, FLS sales manager, explains the difference to other industries: “Metal parts can be manufactured as long as required before delivery. In other words: screws have no best-before date. For this reason, many production planning systems that have proven their worth in a wide variety of industries cannot be used in the food industry – they are not designed to take the shelf life of the products into account. In addition to this criterion, Fekor also includes other food-specific criteria in its planning, for example the planning of the optimum sequence for products between whose production the machines have to be cleaned at great cost.

Another example of how Fekor responds to the special circumstances of the food industry is the consideration of the correct units: During production, Fekor works with liters, kilograms or meters and converts the units into “pieces” during packaging.

Quickly planned and reliably produced

The planning of daily production is a task that requires a great deal of precision and must allow room for change. A planning software adapted to the needs of a processor can plan over 1,000 orders within minutes.

At some point it was no longer possible: the product range was expanded, the machinery grew and the manual detailed production planning with planning board, Excel tables and index cards was hardly manageable. With the production planning software Fekor, Eaton has significantly increased delivery reliability at the Holzhausen and Dausenau plants and at the same time reduced inventories and costs.

Plastics processor publishes Eaton Industries’ user report.
Read more here:

Setup time optimization – made easy by article classification

Minimizing set-up times in production has been a complex and time-consuming issue up to now. However, there is a new way to achieve shorter set-up times more easily and quickly: article classification.

In order to optimize set-up times, matrices were previously set up in which each article appears as a predecessor and as the successor of each other. For example, with 100 articles, such a matrix comprises 100 × 100, i.e. 10,000 cells. The numerical value in each cell represents how much effort it takes to switch from one article to another.

The first filling of the setup time matrix is usually very time-consuming. Later, the maintenance effort is very high, because after a relatively short time it is hardly possible to understand how the individual values came about. The reason for this is that setup times usually depend on several factors, which are summarized in a single numerical value in the setup time matrices.

Only the cause counts

FLS uses a fundamentally different approach for setup time optimization in the production planning system FEKOR – article classification. FLS works with article characteristics, which are individually created depending on the respective process.

The core idea here is always to work out the actual causes for the occurrence of a setup time, because the total time for the setup consists of several parts. Therefore, when changing between articles, the times for converting the machines, cleaning or heating up to a different processing temperature, for example, must be considered separately. FLS illustrates these causes by means of features.

Few features are sufficient

Characteristics can be, for example, the material, its color or the shape of the packaging. The times for changing from one characteristic value to another are entered in a list of characteristics. Here, for example, it is stored that the change of material from A to B or C takes five minutes. For the characteristic “color level”, for example, it is entered that the change from light material to dark material takes eight minutes, but the change from dark material to light material takes twenty minutes.

Important characteristics in an extrusion line are often the mass (PVC or polyethylene), the colour or the temperature profile during processing. In the chocolate industry, characteristics such as “bar colour” (white or not white), “bar mass” (whole milk, bitter, mocha, nut) or “format” (large or small package) are used.

For each production stage, any number of characteristics can be created that are tailored precisely to the respective application. Usually two to five are sufficient.

Characteristic lists are typically created for a specific manufacturing level and there for all affected articles. In this way, you do not have to assign values to hundreds and thousands of individual article combinations. Instead, the values from the corresponding characteristic lists are selected and defined only once for each article.

Changes are quickly implemented

If the time required for setup is reduced, for example, by using a quick-clamping device, only the time for this characteristic is adjusted. All other times for other characteristics remain unchanged. The change then applies immediately to all articles that pass through this process step – without having to adjust each individual article.

Further maintenance is limited to selecting the corresponding characteristic values for new articles. The effort to think through and define all combinations with other articles is completely eliminated.

These are two of the main reasons why work with article classification is significantly faster, simpler and more transparent than with setup time matrices. The author does not know of any other supplier who approaches the topic of setup time optimization in this way.

Once the articles have been classified, it is left to the system to calculate the different combinations and decide which one is the optimum – a classic example of how existing expertise is anchored in a system and the monotonous computing work is then left to the computer. In this way, employees gain time to concentrate on making important decisions or preparing them, for example talking to suppliers about partial deliveries or agreeing on additional shifts or overtime in the event of bottlenecks.

Decisive changes of direction

The article classification takes into account the different duration of the individual work steps: In an extrusion process, for example, where there are different temperature profiles, the temperature is 180 °C for some products and 130 °C for others. Since heating is always faster than cooling, changing from 130 °C to 180 °C takes less time than changing in the opposite direction. When filling beverages, the system takes into account that changing from “Cola” to “Non-Cola” requires more cleaning than changing in the opposite direction.

Realistic times

To minimize setup times, the system analyzes all characteristics for each change and adds the individual times. For simultaneous operations, it uses the respective maximum. It also uses the longer time if a long cleaning process includes a shorter one.

Of course, the system also takes into account that there is no setup time if successive articles have the same characteristic values. For optimization, this means that as many articles as possible with the same characteristics are planned one after the other, and then changes with short setup times are carried out.

Traceable at any time

A further advantage is that all characteristic values are transparent and traceable at all times, because there is a concrete time behind each one. If you later want to check how a setup time came about, you can display the corresponding characteristics and control them easily.

Articles newly included in the user’s production program are only classified once and then incorporated into the entire setup scheme. Only if it becomes necessary to define completely new characteristics does the classification have to be updated once with this new characteristic.

An example from practice

A project at a customer in the rubber industry shows the high benefits of classification: The mixing process for 100 kg of rubber takes six minutes. If the mixer has to be cleaned, it also takes six minutes. If the sequence is not optimally planned, the worst-case scenario is 50 percent plant utilization. If the sequence is planned optimally, for example, cleaning is only necessary after every tenth mixture. The utilization rate can then reach almost 90 percent. In this case, the investment in a new mixer may become superfluous.

When analyzing the set-up times, the most important thing was to determine when the machine only had to be cleaned. One feature was the change from soft rubber to hard rubber, because soft rubber sticks to the dough hook, hard rubber does not. Another criterion was that certain oils, which may be contained in successive compounds, react with each other. Depending on the combination, cleaning had to be carried out when changing from one grade to the other.

Five further criteria were developed in the project. After a few test runs, two more were added and the optimum sequence was then achieved. The development of the characteristics took about half a day, after which the characteristic values were assigned to the individual articles. All in all, the analysis reduced setup time by 35 percent.


Article classification is a valuable tool for optimizing set-up times: In contrast to the set-up time matrices previously used, it is much simpler, faster and more transparent. A major reason for this is that changes in the production process do not require the evaluation of hundreds and thousands of individual article combinations, but rather the selection of values from previously defined feature lists only once for each article. On some systems, this method was used to halve set-up times simply by optimally combining the production sequence.

Author: Dr.-Ing. Hanns Jürgen Hüttner, Managing Director, FLS FertigungsLeitSysteme GmbH & Co. KG, Eschweiler, Germany

Bringing peace into production, regardless of the season

The summer vacation is over, the everyday life has you again. The hustle and bustle before the holiday season and the resettlement stress in the company after the holiday break are almost forgotten. Or at least until the next holiday phase, because more urgent things are coming up.

Sounds familiar? Then FEKOR season planning could be just right for you. It offers companies with seasonal production as well as those with (company) holiday periods the opportunity to bring forward and rectify their production in a meaningful way. So you can look forward relaxed to the holidays with the family or your summer vacation.

We will be happy to provide you with more detailed information on the subject of seasonal adjustment. Please contact us here. If you write us a short note about the situation in your company, we can answer your questions in more detail and send you the appropriate materials.

Dynamic zoom provides an overview in production planning

With the newly developed “Dynamic Zoom”, the production planner can quickly recognize all the consequences that his decisions have on the production process and can thus efficiently minimize set-up times and meet delivery deadlines.

Release 7.0 of the detailed planning software “Fekor” makes production planning for extrusion and injection moulding simpler and clearer. With the newly developed “Dynamic Zoom”, the production planner can quickly recognize all the consequences that his decisions have on the production process and can thus efficiently minimize set-up times and meet delivery deadlines.

The heart of the production planning software Fekor – the control station – was developed by FLS FertigungsLeitSysteme GmbH & Co. KG has now fundamentally revised it and equipped it with a new graphical user interface.

One of the new features is the “Dynamic Zoom”, which makes complex production processes transparent: When the planner wants to analyze a certain order, he activates the zoom with a mouse click and only sees those links that are related to the currently selected process. In this way he does not burden himself with things that are not relevant to his current task; he can make well-founded decisions and act quickly.

Detailed production planning is a highly complex task: even with only 10 orders in front of a workstation, there are 3.6 million different ways to optimize their sequence. In addition, the consequences of a decision usually affect other production stages. This is where the dynamic zoom helps: Everything that is not directly related to an order is hidden.

One of the strengths of the system is that it takes the special features of the plastics industry into account: When extruding plastic, for example, Fekor controls the sequence of colors from light to dark in such a way as to minimize setup times. If sheets or profiles are extruded one after the other with different dimensions, Fekor sorts the products in ascending or descending size and thus also avoids time-consuming set-up work.

Fekor solves the classic conflict in production planning between “reconciling” seemingly contradictory goals: It evaluates all cost-relevant factors at each individual step – personnel, machines and intermediate storage as well as productive and unproductive times – and thus minimizes the overall costs for operation. Priority is always given to ensuring that the promised delivery dates are met.

Production planning and materials management form a single unit in Fekor. In all planning steps and optimizations, the system checks all resources, the availability of personnel as well as material, aids and machines. In this way, the results of the optimization can actually be put into practice.

The new release works under Windows 7 and Oracle 11, and Access 2010 is used as the interface for data maintenance and analyses.