Trialling the Demonstration Phase at End User Sites

During the summer 2017, the PREVIEW system was installed, tested and validated at the facilities of four end users: MPT, PROMOLDING, PROFORM and SRSP. At each demonstrator, the performances of the system were measured following a methodology previously defined by the consortium. Assessing the performance of the subsystems and of the whole system in four real industrial scenarios has been a challenge as the requirements, system specifications and facilities varied from one end-user to the other.

At the four demonstrations, the whole PREVIEW system was successfully installed and the four subsystems correctly communicated with each other and worked all together to form only one PREVIEW system. The end users could finally have access on their smartphones/tablets to all the useful process information provided by the PREVIEW system such as alerts, setup predictions, production and quality control and other static machine information.

The demonstration phase has been an essential step of the PREVIEW project to greatly improve the functioning of each subsystem and to make the PREVIEW system even more performant.


Figure 1: PREVIEW demonstration taking place at a) MPT, b) PROMOLDING, c) PROFORM and d) Smithers Rapra

PREVIEW Whitepaper

Andrea Sánchez-Valencia provides an introduction to the PREVIEW project, from its system as a whole to the four sub-systems that make up the project and testimonials on PREVIEW in action. This whitepaper is a perfect introduction for anybody interested in the system as well as discussing the testing that has occurred to ensure that the system functions as required.

To read PREVIEW’s whitepaper and find out more about the PREVIEW system, please visit this page: Click Here

To view the whitepaper direct, please use this link: Click Here to View Whitepaper

PREVIEW pilot test at Promolding

After developing and small-scale testing the several subsystems for over two years, the partners in the European funded PREVIEW project (Horizon 2020) flew in to perform a full scale pilot test with the PREVIEW system at the Dutch partner Promolding.

Eurecat (Spain), Smithers Rapra (United Kingdom) and Humboldt Universität (Germany) took part in this test. Over a period of three days each team member contributed with its own specialisation in testing the system at Promolding’s new production facility.

DAS Promolding

Figure 1: Injection moulding machine with mould with PREVIEW DAS

During the first day (setup phase) three injection moulding machines were equipped with the PREVIEW data acquisition system (DAS, Figure 1). The DAS is a hardware module responsible for the adaption, amplification and digitalisation of the cavity and machine signals. These signals are supplied by cable to the PREVIEW wireless communication nodes (WCN, Figure 2) located at the machines. The nodes transmit the sensor data to the central wireless node which is connected to the PREVIEW server through Ethernet. This server node was installed in a convenient location on the production floor. All nodes together create a robust wireless network which uses a customised protocol. Also the Bluetooth beacons for the location-based content delivery were positioned throughout the production floor (Figure 3).

On the second day (test phase) the several subsystems were tested. This meant testing the data acquisition system by comparing the signals coming from the injection moulding machine and mould sensors, with the data received from the DAS. Several cables and connections were checked. Also the PREVIEW location based system (LBS) was tested. By checking the physical location on the floor with the virtual location on a floor plan displayed on a smart phone, this subsystem could be verified.


Figure 2: Wireless connection nodes, connected to Ethernet (left) and to DAS (right)

The PREVIEW server, consisting of the advanced predictive system (APS) and the content management system (CMS), and the wireless data transmission were validated by verifying the data reception, processing and storage in the database. The APS is a software algorithm to optimise the injection moulding process by reducing mould set up time and providing a quality control system.

Initially, this test went well, but once more data had been collected the server unexpectedly crashed. After a short period of recuperation from this puzzling situation, four specialists dove deep into the server software and found the stumbling block. The problem was then easily fixed. A true team effort.

In the meantime, to prepare for a life cycle assessment (LCA), some initial measurements of energy consumption of two injection moulding machines were performed, making use of a commercially available energy logger. This data is going to be compared to the data logged through the PREVIEW system to gain insight into the energy savings potentially created by making use of the PREVIEW system.


Figure 3: Bluetooth beacons placed in several locations

The third day was available for doing a full scale test, starting with a Design of Experiments on one of the machines involved. With the data obtained, the APS was trained. The moment of truth arrived: Will the smartphone app indicate a variation in the production process and recommend a process parameter modification when we deliberately alter a parameter on that specific machine? This would mean the whole chain from signal source all the way to a message on a smartphone would work. Success! Once the injection speed was lowered, the app effectively proposed to increase the speed. Happy faces after three days of hard work.

Company Information

Promolding, located in The Hague, The Netherlands, is a product development and injection moulding company established in 1997, that focuses on developing and producing high tech products for the industrial, medical and aviation market. Recently its production facilities have expanded from 1575m2 to 3130m2. Also several dedicated project areas for developing, assembling and testing innovative client specific products, were built up.
With a production force of 12 people (including trial moulders, machine operators, material preparation, assembly and logistics), 12 injection moulding machines ranging from 15T to 800T, dozens of moulds and several materials are prepared and handled for production.
In total Promolding employs 40 people.

Promolding Pano

Figure 4: Part of Promolding’s production facilities where the PREVIEW pilot test was performed

Energy in Injection Moulding

Nowadays identifying the environmental footprint of products and processes is of great importance to determine if they are viable in the long term, or whether they will have negative impacts to human health, non-renewable resources, animals, etc. One way to assess a process is to identify the energy sources and energy amounts that are required to fulfil this. As a very basic definition, energy can be defined as the property that must be transferred to an object to perform work. This means that for an injection machine to function adequately, electrical energy must be transformed into heat and mechanical energies. In the past few years a lot of attention has been given to determine the energy associated with all the various steps in injection moulding. The usual trend observed is that melting of the polymer and clamping of the mould are the steps with the higher energetic contribution.

Table 1. Energy breakdown in percentages for injection moulding of different products (Thiriez, 2006).

Product Melting Injection Clamping Ejector Idle Heaters Cycle time [s]
Dairy container 53% 8% 27% 0% 0% 15% 6.45
Medical Syring 46% 5% 8% 2% 29% 15% 23.1
Pail 50% 10% 13% 0% 15% 11% 18.25
Closure 66% 7% 12% 3% 0% 12% 16.75


The energy can be calculated directly from the monitoring of the equipment’s electrical signal, or alternatively from the cavity’s pressure and temperature information. One of PREVIEW’s main advantages is the fact that real-time data can be obtained directly from the mould, and hence can provide essential information for the calculation of energy consumption estimates.


Thiriez, A. (2006, May). An Environmental Analysis of Injection Moulding. Thesis submitted for the degree of Master of Science in Mechanical Engineering. Massachusetts, Cambridge, United States of America: Massachusetts Institute of Technology.


Initial Wireless Tests at Smithers Rapra and Promolding

An important aspect of PREVIEW is robust wireless communication.  The wireless system is required to transmit sensor information from injection-moulding production cycles from Data Acquisition Systems to the Adaptive Processing Server in a timely manner.  Besides other aspects, the quality of wireless connectivity depends on the environment in which wireless technology is deployed.  The effects of obstruction for example, depend on the materials and geometry of obstructing and surrounding objects.  Typically, metal is the prevalent material in factory environments which can induce less reliable multi-path signal propagation.  Other challenges to reliability are interfering wireless technology and possible noise from machines using high-voltage power.


Whilst it is possible (and useful!) to describe the wireless channel by means of theoretical models, it is important to verify the model’s applicability by true life tests.  Test results may also help to improve parameter selection in order to ensure that the models have a more realistic fit.

Humboldt-University ran a number of transmission tests with wireless hardware designated for the PREVIEW-prototype at Smithers Rapra; the same test was carried out at Promolding.  Amongst the measured parameters were transmission delay, packet delivery ratio and receiver signal strength.


The results will enable a better understanding of the challenges of developing a robust wireless system.  After all, reliability is essential for industrial applications.

ENGEL builds on systems expertise with intelligent temperature control solution

 Fewer rejects and greater energy efficiency

Schwertberg, Austria – June 2016

To mark K 2016, ENGEL has consolidated its systems expertise by expanding its range of intelligent peripherals. The new integrated temperature control solutions include the electronic ENGEL e-flomo temperature control water mani-fold system, temperature control units with speed-controlled pumps and the new iQ flow control software. Taken together, they improve the stability of injection moulding processes, reduce rejects and raise energy efficiency.

Automatically regulating pump capacity

A majority of reject parts produced by injection moulding firms around the world are the result of temperature control errors. With this in mind, temperature control has been a central plank of product and technology development at ENGEL for many years. For K 2010, the machine manufacturer has launched ENGEL flomo, an electronic temperature control water manifold system. Replacing high-maintenance cooling water distributors, the system monitors and documents all cooling and temperature control circuits linked to injection moulds. Moreover, the ENGEL e-flomo development facilitates automatic regulation of the flow rate or temperature difference.

ENGEL is now taking the next step at K 2016. ENGEL e-flomo and temperature control unit merge at controller level to form a single unit. With the help of the new iQ flow control soft-ware, the pump speed is adapted automatically to current requirements based on the measurement values determined by ENGEL e-flomo. While ENGEL e-flomo reduces the risk of rejections by enhancing process stability, less energy is required for temperature control thanks to automatic speed control. Since the pump operates according to need rather than at maximum output all the time, stress on moving parts is reduced and temperature control units have a longer service life.

At its stand, ENGEL will present its new temperature control solution in conjunction with temperature control units made by HB-THERM of St. Gallen, Switzerland, which are sold by ENGEL as an integrated solution.

OPC-UA for maximum data security

The iQ flow control software not only determines the ideal speed in each case, but also makes it possible to operate the ENGEL e-flomo and temperature control unit as an integrated system. All temperature control parameters are set, monitored and logged centrally on the display of the injection moulding machine; the ideal operating point for the particular temperature regulating device is automatically calculated and set.

The CC300 control unit of the ENGEL injection moulding machine and the temperature control unit communicate via OPC-UA (Open Platform Communication Unified Architecture). Based on the complete range of functions of OPC-UA, ENGEL has defined a communications model for temperature control units. The strategy is to open this model to also integrate temperature control units of different suppliers in the future. With its service-oriented, platform-independent and freely scalable structure, this communications model offers very high flexibility while guaranteeing a high degree of data security. Technical safety features are an integral part of the model.

inject 4.0 paves the way to the smart factory

ENGEL uses the prefix iQ to denote intelligent, decentralised assistance systems that enable injection moulding firms to optimise the productivity, efficiency, quality and flexibility of their production. In addition to iQ flow control, this product family includes iQ weight control and iQ clamp control.

Decentralised intelligence is a key feature of continually self-optimising production. With its inject 4.0 range, ENGEL is helping clients pave the way towards the smart factory. Already, inject 4.0 offers numerous solutions for the smart machine, smart production and smart service areas. ENGEL is continually expanding the range. At K 2016, the machine manufacturer will reach a new milestone for the smart machine area with iQ flow control.


ENGEL e-flomo and temperature control unit merge at controller level to form a single unit. With the help of the new iQ flow control software, the pump speed is adapted automatically to current requirements.

ENGEL is one of the global leaders in the manufacture of plastics processing machines. Today, the ENGEL Group offers a full range of technology modules for plastics processing as a single source supplier: injection moulding machines for thermoplastics and elastomers together with automation, with individual components competitive and successful on the market in their own right. With nine production plants in Europe, North America and Asia (China and Korea), and subsidiaries and representatives in more than 85 countries, ENGEL offers its customers the excellent global support they need to compete and succeed with new technologies and leading-edge production systems.


ENGEL AUSTRIA GmbH, Ludwig-Engel-Strasse 1, A-4311 Schwertberg, Austria, tel.: +43 (0)50 620-0, fax: -3009, e-mail:

Digital Revolution in the Manufacturing Industry

On the 3rd February 2016 the High Speed Sustainable Manufacturing Institute (HSSMI) held a forum based on the digital revolution in the manufacturing industry.  This event was designed to highlight connectivity among designers, managers, workers, consumers and physical assets. The following is a summary of the topics presented:

– How collaborative Virtual Environment can innovate manufacturing: The first idea from this presentation was on how to improve communication with the environment.  For instance, sharing files have become more and more complicated due to the barrier files size, different formats, data silos (storage) and insecure data transfer. To overcome this, one solution has been to create a dynamic PDF which will convert CAD files from 45Mo to 3.9Mo.  The second idea involved creating a scan of a factory which would show the facilities, thus enabling a tour to be carried out virtually.  As well as making this a safer option, this virtual tour also offers the possibility of training the operators on the installation and works in a similar way to Google Street view.

– Digital Bill of Process (BOP) – The Future of Manufacturing Engineering: The purpose of this project is to create a part by choosing which materials to use with which process and informing the user of any problems that may occur.

– Integration of virtual and physical production system: Three different projects were presented:

  • Augmented Manufacturing Reality (AMR), this project consists of a scanning flash code to use digital and physical sensor data to obtain a different view of the manufacturing facilities. For example, for the PREVIEW project it would be possible to combine the flash code with the data acquisition system and scan it by opening any application to obtain the temperature and pressure etc. from the machine.
  • Dynamic Resource Monitor (DMR), this project appears similar to the PREVIEW data acquisition system because it is possible to read and record data in real time such as temperature, energy consumption and other multiple combining sensors. It can show the actual data produced from the machine including energy consumption for each production cycle, productive and non-productive energy consumption and waste.
  • SELf – SUStaining Manufacturing Systems (SELSUS) , the focus of this project is about reducing the number of physical prototype models, reducing cost, risk and time, improving quality and knowledge transfer and enhancing visibility. It aims to maximise the performance of the manufacturing process over longer life times to target and timely repair, renovate and upgrade an existing process.

The Purpose of Life Cycle Analysis

Part of the work for Preview requires an assessment of the LCA impact on the new technologies being developed within the project but why are we doing LCA?

LCA is a tool that captures and measures the impact that a product has on the environment. It is able to set up limits, make comparisons, identify hot-spots, or just better understand the impacts on our surrounding natural world.

The life-cycle viewpoint means that we are looking into the whole life of the product: from raw material extraction, through production and usage, up to recycling or disposal – i.e. from cradle to grave. This helps us understand our supply chain and how a change on one side can affect the other.  It also provides assurance that reduction of the environmental impact on one stage in the life cycle does not come at the price of an increase of another stage.

LCA1Within a research project, this translates as a tool that can be used to help decision making in the development stage by comparing different solutions which are otherwise difficult to differentiate. This can also be used to highlight the benefits of the new product compared to existing state of the art and more generally speaking can also be a great communication tool if used correctly!

ENGEL Symposium 2015

During the middle of June the ENGEL Symposium 2015 opened its door to demonstrate at its trade fair stand how machines and production cells can be leveraged to maximum extent thanks to intelligent components and networking.

The ENGEL large-size machine production plant was practically transformed into an injection moulding production facility for this event, where sophisticated components for the automotive, technical moulding, teletronics, packaging and medical industries were produced at new levels of product quality and with previously unseen efficiency.

The latest product was the ENGEL e-connect, a new customer application where injection moulding machines, robots and system solutions are linked via a network, providing a complete overview of the machine park at all times. Machine status, alarm lists, production volume, cycle times and other operating figures are transmitted in real time to a smart phone, allowing the person responsible for the process to immediately initiate corrective measures via the application, without having to be physically present on site. Similarly to ENGEL e-connect, PREVIEW will not only offer a robust wireless network delivering process information to the operator’s mobile device but also the ability to provide the information according to the position of the operator within the plant and his/her role and assigned tasks.

In addition to ENGEL e-connect, two more applications were presented: ENGEL e-calc for the configuration of injection moulding machines according to materials and components being produced and ENGEL plastyfine, the comprehensive image database that not only helps operators identify faults, but at the same time also describes the physical causes and possible technical processing solutions [1]. Like ENGEL e-calc and plastyfine, PREVIEW will also implement an advanced predictive system which in turn will allow for an early identification and characterisation of process deviations and faults.

It is clear that PREVIEW is at the forefront of the current and future challenges of the injection moulding industry and thanks to its flexibility, easy installation and performance will offer a middleware solution, not just for plastic injection manufacturing processes but for any manufacturing process requiring compact and universal data acquisition systems and cutting edge production control expert systems.

This pre-commercial technology which is both universal and greener, will aim to reduce mould set up time by 50%, reduce waste and energy consumption by 20% and increase productivity and flexibility by 30%.

[1] Engel, 2015. Press release [online]. Available from

Injection Moulding Process: Mould and Process Optimisation

Plastic injection moulding is widely acknowledged as being the manufacturing technique to produce highly complex geometric plastic parts at low cost. The quality of the final product is heavily dependent upon careful selection of processing conditions and material selection which in turn is used to perform design analysis and dimensioning of the mould (Figure 1).

Figure 1

Figure 1 : Optimisation of injection moulding process

An inadequate selection of set process conditions is known to cause a decrease in product quality as a result of defective final products due to residual stresses, warpage, voids, sink marks, etc. Cavity pressure and mould temperature are of paramount importance for optimisation of the injection moulding process as these have a direct effect on the quality of the final product [1]. For example, higher mould temperatures with amorphous polymers such as ABS and PC have been shown to produce lower stress levels, leading to improved impact and stress-crack resistances and fatigue performances [2].

When moulding semi-crystalline materials, it has been reported that mould temperature should be kept higher than glass-transition temperature, allowing sufficient time for the polymer to crystallise. Overall, it has been found that lower melt temperatures in conjunction with higher mould temperatures tend to provide improved quality performance.

However, most injection machines are often operated at higher temperatures in an attempt to reduce melt viscosity.  When increasing temperature the viscosity reduces and it is this higher temperature which could lead to increased degradation, cooling time and energy consumption. It has been shown that an injection moulding machine in idle mode with no production consumes 80% of the full load power [3], whilst cooling represents approximately 10-15% of the total energy used.

The design of the mould plays an important role when examining polymer processability and its effect on energy consumption. Moulded parts with thinner walls, particularly suitable for fibre-reinforced thermoplastics (FRPs), require shorter cycles and compare more favourably in terms of energy. A reduction in the moulded part wall thickness of 25% has been shown to reduce cooling time by more than 40% [4].

It has also been found that uniform temperature distribution within the mould maximises efficiency. As a result, conformal water lines have been used by using selective laser melting technology (SLM) because of their ability to perfectly shape according to the moulding surface. This ensures a more uniform mould temperature distribution, improving quality of the final product (Figure 2) [5].

Figure 2

Figure 2 : SLM and conformal channels [5]

The application of high performance alloys for mould design provides another potential solution for the optimisation of the injection moulding process (Figure 3). This fabrication method enables a unique combination of strength and thermal conductivity that offers important benefits such as shorter cycle time and improved part quality [6].

Figure 3Figure 3 : Example of a copper alloy mould design [4]

Pulsed cooling is also a reliable approach for the optimisation of the cooling phase of the injection moulding process when compared to continuous cooling [7], leading to reduced cycle times (approximately 20% reductions) and lower energy consumptions.

By judicious selection of materials, mould design and processing conditions it is clear that injection moulding processes can be optimised without any reduction in quality performance. Therefore, an understanding of the energy consumption of the injection moulding process and its relationship to set process conditions, mould design and polymer being used may result in potential energy savings. It has been shown that simple no cost or low cost energy practices can reduce energy consumption by between 10 and 20%, which would result in product cost savings of £38 million per annum [8].


[1] H. Hassan, An experimental work on the effect of injection molding parameters on the cavity pressure and product weight, International Journal of Advance Manufacturing Technology, Vol. 67, pp 675- 685, 2013.

[2] M. Sepe, The importance of Melt & Mold temperature, Plastics Technology, December, 2011

[3] R. Kent, Energy Management in Plastics Processing, Plastics Information Direct, Bristol, 2008

[4] D. Godec, Processing parameters influencing energy efficient injection moulding of plastics and rubbers, Polimeri, Vol.33, pp 112-117, 2012

[5] Inglass, Mold conditioning optimization and SLM-Selective Laser Melting technology, available from:

[6] J. C. J Kuli and R. Kusner, A review of Copper Alloys for Plastic Injection Molding, Plastics Technology, December, 2011

[7] A. G. Smith et al, Optimisation of Continuous and Pulsed Cooling in Injection Moulding Processes, Plastics, Rubber and Composites, 36, pp 93 -100, 2007

[8] R. Kent, Energy management in plastics processing – framework for measurement, assessment and prediction. Plastics, Rubber and Composites, Vol.37, pp 96 -104, 2008