Ahlm case study
The AHLM logo

Helping AHLM add value by optimising data usage

AHLM is a Swedish company developing, producing, and selling material containers, mixing machines and mobile plants for handling dry mortar, mortar, floating putty and similar materials. Their machinery is used by construction businesses in the Nordic region. They also offer their customers service, support and repair for their machinery.

IndustryConstruction machinery and services
Websitehttps://www.ahlmmaskin.se/
Business focusB2B
Areas of operationSweden and the Nordic region
Product portfolioMortar and putty material containers, pump trucks, mixing machinery, mobile flotation machinery, saws and accessories

The Story

Pump trucks are one of the main products AHLM offer their customers. These trucks are used on construction sites to put mortar, putty etc., mix and transport them to construction locations.

These pump trucks have a mixing room and machine room manufactured in sandwich panels coupled with a 1000-litre water tank and hose reels. Each pump truck has a PLC (Programmable Logical Controlling unit) with a touch panel that allows the operator to process overviews, control the pump truck operations, access operation settings, get measurements, undertake recipe management, print reports etc.

Having a plethora of real-time data generated through IoT devices at their disposal, AHLM wasn‘t utilising this data in the most optimal manner that would add value to their customers.

A screenshot the AHLM mobile app

AHLM‘s Objectives

  • Gather real-time data from pump trucks and create a centralised repository.
  • Deliver real-time insights to clients on the progress of their projects at construction sites.
  • Establish an easy mechanism for customers to sign off on pump truck deliveries on site.
  • Harness the potential of real-time data from sites to market the scale of operations.

Challenges and Solutions

Villvay devised a hybrid app which works on both web and mobile to help AHLM meet its objectives. The app was developed using Python, React, and Java Spring Boot, and is hosted on Google Cloud.

Challenge

AHLM has more than 100 operational Pump trucks with PLCs that generate two types of reports: machine reports and time reports. A pump truck generates around 1 -3 reports that are stored as raw data in several locations. This makes it hard for any user to retrieve them and make sense of them.

Solution

Developed a workflow that captures and stores all pump truck data on the Cloud. This makes the data easily accessible through an intermediary API.

Challenge

The data generated through pump trucks were in a raw format that was unreadable by customers and business users of AHLM.

Solution

Data visualisation and creating a client dashboard that gets updated in real-time. This visualised client dashboard provided information on individual projects, water used, pump times, temperature, capacity, generating custom reports etc. This dashboard was presented to clients through a multilingual web app and a mobile app with individual logins.

Challenge

With the development of the client information dashboards, admins of AHLM required a centralised mechanism to easily connect Pump truck data to its related customers in the back office.

Solution

Developed an admin dashboard that lets users add, remove and edit pump trucks and customers and generate tokens for individual trucks.

Challenge

Customer sign-off on pump truck projects was a manual and timely activity for AHLM with a lot of room for error and misplaced information.

Solution

With the mobile app, customers were able to instantly review information on the project and sign off on it through a digital signature, all of which were stored on the cloud.

Challenge

To attract new customers, AHLM needs to give potential customers a preview of what‘s in store, using the data they‘ve gathered.

Solution

Developed a public dashboard as a web app that collates information from all pump trucks in real-time. It also reveals general statistics to anyone who visits the site without logging in.

The Results

  • Data collected and visualised from more than 100 pump trucks
  • More than 1000 projects completed.
  • More than 1000 custom reports generated.