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How to turn a fish-processing facility into a super-efficient enterprise

The case of increasing staff productivity by 40% with CVC neural network video analytics
Buying expensive equipment and investing in modern software often does not lead to increased productivity, because people remain the key obstacle to progress. You can replace a machine, but the staff's approach to their work won't change at the snap of a finger. Unfortunately, the fish processing industry is no exception, but artificial intelligence and neural network technology are coming to the rescue. In this case study you will learn about the results achieved during the implementation of CVC neural network video analytics in one of the fish processing plants.
Contents list
The specifics of this case is that it was the first implementation at an enterprise in this market segment. As a rule, when we implement the first ten objects of one niche, the companies of the industry, communicating with each other and getting a positive reference, come to us by the principle of "word of mouth". But when the field is new to us, as it turned out with this fish processing company, the client simply leaves an application on our website...

    The essence of the problem or how it all began

    The customer for this case is a full-cycle fish-processing facility: from incoming fish to finished canned fish, seafood cocktails, and fish snacks.

    The company opened a tender to find a contractor in the field of neural network analytics and machine vision for two of its separate branches. In doing so, each branch solved its own problems and made an independent decision to select a future contractor. As a result, one branch, headed by the risk management department, chose our company, while the other (headed by the production manager) went with a different company. Looking ahead, it should be noted that our neural network analytics had already been implemented at six sites in four production buildings of the company, while the project of the second branch had not started yet (it had been a year!).

    Communication with a new customer always starts with our question: "What problem do you want to solve with video analytics?" Then we focus the question on this problem and ask to show a video or photo report to understand the specific business process. In this case, our experience allows us to determine already at the first meeting not only how we can solve the problem, but also to orient on the price.
    Our company is the only one in the market of production video analytics with an approved price list. A large track list of implemented projects enables us to standardize the cost of case implementation, instead of calculating it every time at a new site.
    The client's problem was to find possible options for automation of accounting. As a consequence, to reduce the cost of maintaining middle management (control and audit group, accountants, senior shifts and CAG). That is, it was a question of reducing the staff that is not involved in production, but performs the functions of "through" and selective control. And this is exactly what our neural network robots can effectively do.

    Project integration (implementation) features

    Integration is the process between the signing of the contract and the transfer of the finished solution to the client.

    In this case, the training of neural network robots, setting up a personal account for the customer (in which you can monitor the work of your company from anywhere in the world) takes 3-4 times less time than that for the issues of coordination: specifications, equipment, places of its installation, the accuracy of control metrics and the contract. And the duration of this period is due to the approval procedures adopted at the customer's enterprise.

    The implementation process itself took less than two months and consisted of several stages.

    Survey stage. At this stage we determine the feasibility of using the company's current video surveillance system (VSS) to implement neural network video analytics. The task of our engineers is to make a simple conclusion - whether we can use the existing VSS, whether it needs to be changed or partially updated (for example, the recorder is suitable, but the camera needs to be replaced). The client receives a specification with a list of necessary equipment, if upgrading is still required. But in most cases we use a system that is already available in the enterprise.

    In this case, no modernization was required, we used the customer's existing equipment.

    Robot training phase. The stage of training the robot, which interacts with the video system of the object, identifying what is happening in the video. After that, the robot begins to "understand" what is in the video and what is not, on the basis of which the relevant reports are generated. As a result, the customer is conveniently informed about all violations with video confirmation of each event.
    Integration stage with the customer's internal accounting systems (e.g., warehouse system). Integration is required only with those cases where synchronization with the accounting system data is required. For example, the customer's accounting system records how many tons of uncut fish came on the conveyor and how many came off the conveyor already in the form of fillets, which needs to be recalculated.

    It is important to clarify that we never interfere with the client's accounting system. But we organize a secure connection, which allows exchanging pre-agreed information via a buffer. This approach is the best practice not only in terms of reliability and speed of implementation, but also in terms of information security for the client company.

    Creation of such buffers requires the involvement of qualified professionals from the customer. For our part, of course, we help, as we are interested in the implementation of the project.

      What tasks our CVC solved

      All tasks are in one way or another related to the company's business processes. And the more accurately these business processes are defined, the easier it is for the system to detect deviations. At a fish processing company, our neural network video analytics was able to close the following tasks:

      1. Control of washing units: counting of washed containers

      Such food production facilities, which receive raw materials in the form of meat or fish products, are faced with an obligatory process - washing containers. The containers can be different (huge barrels, buckets, small boxes) and depending on the type of containers, pieceworkers are paid accordingly.

      Before the system was implemented, data on the actual quantity of washed containers were obtained from the executives, which led to intentional and unintentional distortions. After the implementation of neural network video analytics, the customer began to receive data on employee output with an accuracy of over 98%. All the data was confirmed by slicing the corresponding video footage, which could be used on occasion.

      According to the results of the CVC system operation, the overestimation of the wage fund by more than 40% was revealed. The economic effect for the enterprise was more than 5400 USD per month.
        Note that our company implemented the "Container Washing" module with 99.9% implementation of the client's wishes in five weeks.

        For comparison, a competitive company evaluated this module in several months and with 80% implementation of the client's wishes.

        2. Counting the number of products that have passed on the conveyor (any type of product is counted: fillets/fish on peaks; sliced fillets, portions of fish on a substrate)

        Implementation of this type of control allowed the customer to obtain accurate data on the number of products produced per shift.
        More in-depth control of the products produced by each employee on the shift enabled the company to, among other things:
        • plan raw materials and conveyor loading;
        • fairly calculate wages;
        • increase staff productivity through training, replacement, and motivation.
        Moreover, employees, realizing that their pay depends solely on their actions and that the company now has an automated control system, began to increase their output.

          3. Control of compliance with discipline

          The system makes a record of the time of arrival and departure of staff, time spent at the workplace, which also increases discipline and affects productivity.
            As a result of the implementation, the customer reduced three staff units with a total payroll of 4400 USD/month (bookkeepers), and one staff unit with a payroll of 1200 USD/month (quality controller).

            One of the challenges of implementing neural network video analytics in the fish processing industry

            As for the specifics of the industry, we should note the presence of the so-called demountable lines. We first encountered the assembling and disassembling of lines in fish production.

            The point is that the production is equipped with a large number of light conveyor lines, which, about once a month, are completely disassembled for washing and then reassembled. Accordingly, the first assembly after washing and ... all the equipment was not assembled where it was originally (a meter to the right or left or changed the configuration). Despite the fact that we discussed this point at the start of the integration, but in practice the situation still occurred. The line was re-assembled, and then we put the key marks on the floor, which determined how the lines should be assembled after each wash.

            There are other nuances, such as shops with high humidity, with a lot of steam and condensation, which affects the placement of CCTV cameras. Each production has its own nuances, but they are all solved.

            We especially love clients who are willing to set industry standards

            This is now a standard case for us, and subsequent implementations at three fish processing companies have gone even faster. But each new area is incredibly interesting for us, especially if the client is ready to create production trends in his area.

            One of the principles of our work is to reduce the cost of video analytics implementation as much as possible. The goal is to make the project as passable as possible for the company from the point of view of financial efficiency. And in most cases such answers are found together with the customer. For example, if the customer has 10 tasks, 9 of which make up 10% of the budget, and another 90%, we try to decide together how to make this one cheaper, or the customer can refuse from it. In the joint work it is important to clarify which issues will give the best result.

            What we are proud of

            Modesty is said to be more trustworthy. We believe that it is the facts and the results that are trustworthy.
            • 1
              We have implemented more than a hundred projects in various industries: from bakeries to logistics centers to automobile businesses. There is no other company on the Russian market that can boast of such a large number of projects.
            • 2
              We provide affordable cost of both implementation and use. Our ideology, our mission is the creation of industrial standards for neural network analytics. The creation of an industrial standard implies its affordability. Its accessibility in terms of speed and resources, including money.
            Still thinking about it? You can ask for references about us from companies in your industry. We are happy to share our customer contacts from whom you can learn everything you need to know to make a decision.
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