Unlock Tips for Using the Founder Chuangliu System to Automatically Complete 90% of Layout Tasks
Nowadays, digitalization, automation, and intelligence have become the direction and consensus for the printing industry. As the mainstream choice for domestic party newspaper printing factories, the Founder Chuangliu System acts as an accelerator for intelligent production, with a market share as high as 90%. But how do you actually get this powerful system to "run smoothly" and achieve fully automatic layout? This article will share some practical experience and take you behind the scenes.
File Naming Rules for Layouts
The core of the Founder Chuangliu System (Figure 1) lies in using scripts to achieve fully automatic layout, and the key to this is hidden in the file naming rules for layouts. Take the Hubei Daily as an example, its layout file naming rule is: 20250112xxhbrba0001c.pdf. The first eight digits represent the year, month, and date; "xxhbrb" represents the newspaper name; "a" stands for the edition name; "0001" is the page code, and for general sections, like pages 6–7, the code would be "0607"; "c" indicates color. Only by thoroughly understanding these elements can we accurately write scripts.
Figure 1: Founder Changliu System Client Interface
Custom Scripts
In the script editing interface, click the "+" sign to add a script, and you can name it whatever you like. Once you enter the editing interface, as shown in Figure 2, the first column is "Analysis Stack Name." A stack name is the name we set when making a plan, as shown in Figure 3. It's usually represented by uppercase or lowercase letters, but you can also use Chinese names like "First Stack" or "Special Issue." For newspapers with simple operations, the "Analysis Stack Name" can be omitted without affecting automatic layout; for more complex newspapers, like the Hubei Daily, they normally use Stack A, but during special periods, they might use Stack B and Stack T, so the "Analysis Stack Name" is very important.
Figure 2 Script Editing Interface
Figure 3 New Collation Interface
The Fangzheng Changliu system's scripts support JavaScript. In the function GetFoldName(inputName), inputName represents the string parameter passed in, which is the name of the layout file (excluding the .pdf extension). Here's a simple code example:
Var index = inputName.search(/hbrb/i);
if(index > -1){
var fold = inputName.slice(index + 4, index + 5);
return fold.toUpperCase();
}
The first line uses inputName.search(/hbrb/i) to search for the feature string "hbrb" in the file name and assigns the result to the variable index. The 'i' in the regular expression /hbrb/i means case-insensitive, ensuring that the code works whether the file name is uppercase, lowercase, or mixed case.
The second line checks if the feature string was found. If found, index will be greater than -1.
The third line extracts the fold name using the slice method. The first parameter of slice specifies the start position and the second parameter specifies the end position. Here, it starts from the 4th character after "hbrb" and extracts up to the 5th character (which is the fold name).
The fourth line converts the fold name to uppercase and returns it to the system.
Next is "Analyzing Edition Number," which is the most critical part of the script. The code is as follows:
var index = inputName.search(/hbrb/i);
if(index > -1){
var page = inputName.slice(index + 7, index + 9);
return parseInt(page, 10);
}
The parseInt function converts the extracted edition string into a number and returns it to the system.
With this code, we can not only achieve automatic layout collating, but also automatically place files in an unrecognized area when the collating staff selects the wrong file, avoiding mistakes in automatic collating and improving CTP production efficiency.
In short, once you master these tricks, you can handle 90% of newspaper intelligent collation tasks by applying the same principles. If you encounter more difficult coding problems, we can consult AI large models like Kimi or Tongyi. With the support of AI large models, even coding enthusiasts can reach the level of professional programmers. In the future intelligent society, being able to solve problems using AI large models will be a basic skill for company elites.