By Stepwise
Client
Stabilis
Project BackgroundManufacturing efficiency in factories is subject to a wide range of constantly changing factors. Machine operators and other qualified production workers need to keep monitoring the particular stages of production and, if need be, respond appropriately and immediately… These manual technical activities may take a few hours, generating bottlenecks in the manufacturing process. Companies are then to a large extent dependent on the experience and skills of their staff. Stabilis, a company specializing in intelligent applications for Industry 4.0, decided to resolve these issues with our help.Main ChallengeOur task was to create an algorithm to take values from the manufacturing machine and advise when and how settings should be altered. One of the challenges in this project was the fact that gathering and processing additional data (particularly data coming from the surroundings) was not possible. An additional algorithm was necessary to identify if any available sets of data contained data essential for the main algorithm, and then to select that data.Our ApproachThe first step was to check and analyze the data the customer possessed. Our team developed an algorithm that signaled the need to alter parameters and settings of a manufacturing machine, and then indicate which of those will facilitate production.Python and Scikit-learn libraries were used for developing the software, and the entire software solution was packaged into a Docker image and given to the customer with complete documentation.Final OutcomeThe Stepwise team created algorithms that are able to suggest parameters required to change the settings of manufacturing devices. Using this technology, manufacturing companies are now able to considerably and rapidly adjust appropriate settings for their machines, which enhances production effectiveness and saves on raw materials and other consumables.
Project BackgroundManufacturing efficiency in factories is subject to a wide range of constantly changing factors. Machine operators and other qualified production workers need to keep monitoring the particular stages of production and, if need be, respond appropriately and immediately… These manual technical activities may take a few hours, generating bottlenecks in the manufacturing process. Companies are then to a large extent dependent on the experience and skills of their staff. Stabilis, a company specializing in intelligent applications for Industry 4.0, decided to resolve these issues with our help.Main ChallengeOur task was to create an algorithm to take values from the manufacturing machine and advise when and how settings should be altered. One of the challenges in this project was the fact that gathering and processing additional data (particularly data coming from the surroundings) was not possible. An additional algorithm was necessary to identify if any available sets of data contained data essential for the main algorithm, and then to select that data.Our ApproachThe first step was to check and analyze the data the customer possessed. Our team developed an algorithm that signaled the need to alter parameters and settings of a manufacturing machine, and then indicate which of those will facilitate production.Python and Scikit-learn libraries were used for developing the software, and the entire software solution was packaged into a Docker image and given to the customer with complete documentation.Final OutcomeThe Stepwise team created algorithms that are able to suggest parameters required to change the settings of manufacturing devices. Using this technology, manufacturing companies are now able to considerably and rapidly adjust appropriate settings for their machines, which enhances production effectiveness and saves on raw materials and other consumables.
Project BackgroundInternational flights require landing and overflight permits. Currently, all documentation is created manually, which increases the possibility of human error. There was a strong need to improve the entire permit application process.Main ChallengeThe main goal was to create a solution that would solve the problem of creating permits manually. 3,000 permits are obtained every year which require 10,000 documents, of which one carrier is approximately 80 aircraft.The serious consequences of incorrect applications, such as delays and flight cancellations, generate huge losses and become a challenge.The question was how to create a reliable and useful solution that would meet all the requirements of such a demanding industry? Our ApproachOur Product Design team proposed an individually selected UX design process. We began with a Discovery phase to get to know the client’s requirements and needs. Thanks to this, we gathered the necessary knowledge for us to group and identify areas in which to streamline the entire process of obtaining flight permits.As a result we were able to design an interactive prototype with powerful functionalities to satisfy the users’ goals.Usability tests carried out with a target group allowed us to finally confirm the intuitiveness and usability of the application. This gave our client the confidence that the whole initiative was going into the right direction. Final Outcome"The application process is simple, easy and intuitive", replies one of the respondents, which confirms to us that the process we chose was necessary in creating a valuable product. The client had a great idea and our Product Design team turned it into a valuable solution.As a result, we were able to successfully deliver an interactive prototype which became the foundation for MVP. This then allowed the client to present the product to potential investors and customers within just 3 months!
Project BackgroundLecko is management consulting company that facilitates digital transformation processes and analytics. They do it by analyzing qualitative data related to actions taken by people in their working environment. Main challengeIntegrating Lecko’s existing analytical systems with business solutions providers such as Office 365 and GSuite. Our Approach We conducted a thorough technical audit of the currently used systems and implemented cloud solutions based on GCP and Azure. The project involved a full configuration of the cloud infrastructure as well as performace improvements in the existing systems to allow real-time processing of large data quantities. Final OutcomeThanks to our help, Lecko was able to successfully move all their analytics to the cloud, which in turn boosted up the overall system performance. By reducing Time to Market, they can now react faster to the inreasing client demand, which was much needed given that their analytical platform provides currently business services to around 20 organizations willing to accelerate their digital transformation. TechnologyGoogle Cloud PlatformAzureJavaMongoDBBigQuery
Project BackgroundSpica Technologies Ltd is a global prop-tech company, offering services and technologies for the management of properties, facilities and building equipment. The main area of cooperation with Stepwise is developing a cloud-based platform for workplace experience management. The Main ChallengeThis Stepwise customer already had web and mobile digital products developed using one of the newer technologies available in the market from Google – the Flutter framework. This decision was associated with several important facts:● Software created with Flutter is future-proof.● With just one codebase, a customer can produce software for several operating systems and devices, which facilitates time-to-market and reduces costs incurred by making a few versions of one product.● There are very few companies offering reliable support in developing software with this new technology. Our ApproachAt the beginning of our cooperation with Spica Tech, we chose two experts in mobile and web solutions from our team to provide our customer with competences combining technical knowledge and extensive experience in software development. We knew that efficient work and effective cooperation with open source communities would be very important in that project. Three months later we had a solid basis for developing that IT project. Our experts prepared the essential foundations for cooperation with Spica Tech and the Google team. That time allowed us to get to know our customer’s expectations and business needs. We prepared a set of best practices for that project and actively supported our customer. We also engaged our UX/UI designer.Final OutcomesAfter almost a year, the partner cooperation between Spica Tech and Stepwise resulted in a great mobile application for the insurance industry.Stepwise specialists felt comfortable in the Spica Tech structures and offered high availability, reliability and comprehensive support in developing the software.